Publications

Displaying 1 - 100 of 110
  • Adank, P., Smits, R., & Van Hout, R. (2003). Modeling perceived vowel height, advancement, and rounding. In Proceedings of the 15th International Congress of Phonetic Sciences (ICPhS 2003) (pp. 647-650). Adelaide: Causal Productions.
  • Akamine, S., Kohatsu, T., Niikuni, K., Schafer, A. J., & Sato, M. (2022). Emotions in language processing: Affective priming in embodied cognition. In Proceedings of the 39th Annual Meeting of Japanese Cognitive Science Society (pp. 326-332). Tokyo: Japanese Cognitive Science Society.
  • Anastasopoulos, A., Lekakou, M., Quer, J., Zimianiti, E., DeBenedetto, J., & Chiang, D. (2018). Part-of-speech tagging on an endangered language: a parallel Griko-Italian Resource. In Proceedings of the 27th International Conference on Computational Linguistics (COLING 2018) (pp. 2529-2539).

    Abstract

    Most work on part-of-speech (POS) tagging is focused on high resource languages, or examines low-resource and active learning settings through simulated studies. We evaluate POS tagging techniques on an actual endangered language, Griko. We present a resource that contains 114 narratives in Griko, along with sentence-level translations in Italian, and provides gold annotations for the test set. Based on a previously collected small corpus, we investigate several traditional methods, as well as methods that take advantage of monolingual data or project cross-lingual POS tags. We show that the combination of a semi-supervised method with cross-lingual transfer is more appropriate for this extremely challenging setting, with the best tagger achieving an accuracy of 72.9%. With an applied active learning scheme, which we use to collect sentence-level annotations over the test set, we achieve improvements of more than 21 percentage points
  • Bauer, B. L. M. (2022). Finite verb + infinite + object in later Latin: Early brace constructions? In G. V. M. Haverling (Ed.), Studies on Late and Vulgar Latin in the Early 21st Century: Acts of the 12th International Colloquium "Latin vulgaire – Latin tardif (pp. 166-181). Uppsala: Acta Universitatis Upsaliensis.
  • Bauer, B. L. M. (2003). The adverbial formation in mente in Vulgar and Late Latin: A problem in grammaticalization. In H. Solin, M. Leiwo, & H. Hallo-aho (Eds.), Latin vulgaire, latin tardif VI (pp. 439-457). Hildesheim: Olms.
  • Bentz, C., Dediu, D., Verkerk, A., & Jäger, G. (2018). Language family trees reflect geography and demography beyond neutral drift. In C. Cuskley, M. Flaherty, H. Little, L. McCrohon, A. Ravignani, & T. Verhoef (Eds.), Proceedings of the 12th International Conference on the Evolution of Language (EVOLANG XII) (pp. 38-40). Toruń, Poland: NCU Press. doi:10.12775/3991-1.006.
  • Bowerman, M. (1983). Hidden meanings: The role of covert conceptual structures in children's development of language. In D. Rogers, & J. A. Sloboda (Eds.), The acquisition of symbolic skills (pp. 445-470). New York: Plenum Press.
  • Brand, J., Monaghan, P., & Walker, P. (2018). Changing Signs: Testing How Sound-Symbolism Supports Early Word Learning. In C. Kalish, M. Rau, J. Zhu, & T. T. Rogers (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (CogSci 2018) (pp. 1398-1403). Austin, TX: Cognitive Science Society.

    Abstract

    Learning a language involves learning how to map specific forms onto their associated meanings. Such mappings can utilise arbitrariness and non-arbitrariness, yet, our understanding of how these two systems operate at different stages of vocabulary development is still not fully understood. The Sound-Symbolism Bootstrapping Hypothesis (SSBH) proposes that sound-symbolism is essential for word learning to commence, but empirical evidence of exactly how sound-symbolism influences language learning is still sparse. It may be the case that sound-symbolism supports acquisition of categories of meaning, or that it enables acquisition of individualized word meanings. In two Experiments where participants learned form-meaning mappings from either sound-symbolic or arbitrary languages, we demonstrate the changing roles of sound-symbolism and arbitrariness for different vocabulary sizes, showing that sound-symbolism provides an advantage for learning of broad categories, which may then transfer to support learning individual words, whereas an arbitrary language impedes acquisition of categories of sound to meaning.
  • Bruggeman, L., Yu, J., & Cutler, A. (2022). Listener adjustment of stress cue use to fit language vocabulary structure. In S. Frota, M. Cruz, & M. Vigário (Eds.), Proceedings of Speech Prosody 2022 (pp. 264-267). doi:10.21437/SpeechProsody.2022-54.

    Abstract

    In lexical stress languages, phonemically identical syllables can differ suprasegmentally (in duration, amplitude, F0). Such stress
    cues allow listeners to speed spoken-word recognition by rejecting mismatching competitors (e.g., unstressed set- in settee
    rules out stressed set- in setting, setter, settle). Such processing effects have indeed been observed in Spanish, Dutch and German, but English listeners are known to largely ignore stress cues. Dutch and German listeners even outdo English listeners in distinguishing stressed versus unstressed English syllables. This has been attributed to the relative frequency across the stress languages of unstressed syllables with full vowels; in English most unstressed syllables contain schwa, instead, and stress cues on full vowels are thus least often informative in this language. If only informativeness matters, would English listeners who encounter situations where such cues would pay off for them (e.g., learning one of those other stress languages) then shift to using stress cues? Likewise, would stress cue users with English as L2, if mainly using English, shift away from
    using the cues in English? Here we report tests of these two questions, with each receiving a yes answer. We propose that
    English listeners’ disregard of stress cues is purely pragmatic.
  • Bujok, R., Meyer, A. S., & Bosker, H. R. (2022). Visible lexical stress cues on the face do not influence audiovisual speech perception. In S. Frota, M. Cruz, & M. Vigário (Eds.), Proceedings of Speech Prosody 2022 (pp. 259-263). doi:10.21437/SpeechProsody.2022-53.

    Abstract

    Producing lexical stress leads to visible changes on the face, such as longer duration and greater size of the opening of the mouth. Research suggests that these visual cues alone can inform participants about which syllable carries stress (i.e., lip-reading silent videos). This study aims to determine the influence of visual articulatory cues on lexical stress perception in more naturalistic audiovisual settings. Participants were presented with seven disyllabic, Dutch minimal stress pairs (e.g., VOORnaam [first name] & voorNAAM [respectable]) in audio-only (phonetic lexical stress continua without video), video-only (lip-reading silent videos), and audiovisual trials (e.g., phonetic lexical stress continua with video of talker saying VOORnaam or voorNAAM). Categorization data from video-only trials revealed that participants could distinguish the minimal pairs above chance from seeing the silent videos alone. However, responses in the audiovisual condition did not differ from the audio-only condition. We thus conclude that visual lexical stress information on the face, while clearly perceivable, does not play a major role in audiovisual speech perception. This study demonstrates that clear unimodal effects do not always generalize to more naturalistic multimodal communication, advocating that speech prosody is best considered in multimodal settings.
  • Byun, K.-S., De Vos, C., Roberts, S. G., & Levinson, S. C. (2018). Interactive sequences modulate the selection of expressive forms in cross-signing. In C. Cuskley, M. Flaherty, H. Little, L. McCrohon, A. Ravignani, & T. Verhoef (Eds.), Proceedings of the 12th International Conference on the Evolution of Language (EVOLANG XII) (pp. 67-69). Toruń, Poland: NCU Press. doi:10.12775/3991-1.012.
  • Cambier, N., Miletitch, R., Burraco, A. B., & Raviv, L. (2022). Prosociality in swarm robotics: A model to study self-domestication and language evolution. In A. Ravignani, R. Asano, D. Valente, F. Ferretti, S. Hartmann, M. Hayashi, Y. Jadoul, M. Martins, Y. Oseki, E. D. Rodrigues, O. Vasileva, & S. Wacewicz (Eds.), The evolution of language: Proceedings of the Joint Conference on Language Evolution (JCoLE) (pp. 98-100). Nijmegen: Joint Conference on Language Evolution (JCoLE).
  • Chen, A. (2003). Language dependence in continuation intonation. In M. Solé, D. Recasens, & J. Romero (Eds.), Proceedings of the 15th International Congress of Phonetic Sciences (ICPhS.) (pp. 1069-1072). Rundle Mall, SA, Austr.: Causal Productions Pty.
  • Chen, A. (2003). Reaction time as an indicator to discrete intonational contrasts in English. In Proceedings of Eurospeech 2003 (pp. 97-100).

    Abstract

    This paper reports a perceptual study using a semantically motivated identification task in which we investigated the nature of two pairs of intonational contrasts in English: (1) normal High accent vs. emphatic High accent; (2) early peak alignment vs. late peak alignment. Unlike previous inquiries, the present study employs an on-line method using the Reaction Time measurement, in addition to the measurement of response frequencies. Regarding the peak height continuum, the mean RTs are shortest for within-category identification but longest for across-category identification. As for the peak alignment contrast, no identification boundary emerges and the mean RTs only reflect a difference between peaks aligned with the vowel onset and peaks aligned elsewhere. We conclude that the peak height contrast is discrete but the previously claimed discreteness of the peak alignment contrast is not borne out.
  • Cheung, C.-Y., Yakpo, K., & Coupé, C. (2022). A computational simulation of the genesis and spread of lexical items in situations of abrupt language contact. In A. Ravignani, R. Asano, D. Valente, F. Ferretti, S. Hartmann, M. Hayashi, Y. Jadoul, M. Martins, Y. Oseki, E. D. Rodrigues, O. Vasileva, & S. Wacewicz (Eds.), The evolution of language: Proceedings of the Joint Conference on Language Evolution (JCoLE) (pp. 115-122). Nijmegen: Joint Conference on Language Evolution (JCoLE).

    Abstract

    The current study presents an agent-based model which simulates the innovation and
    competition among lexical items in cases of language contact. It is inspired by relatively
    recent historical cases in which the linguistic ecology and sociohistorical context are highly complex. Pidgin and creole genesis offers an opportunity to obtain linguistic facts, social dynamics, and historical demography in a highly segregated society. This provides a solid ground for researching the interaction of populations with different pre-existing language systems, and how different factors contribute to the genesis of the lexicon of a newly generated mixed language. We take into consideration the population dynamics and structures, as well as a distribution of word frequencies related to language use, in order to study how social factors may affect the developmental trajectory of languages. Focusing on the case of Sranan in Suriname, our study shows that it is possible to account for the
    composition of its core lexicon in relation to different social groups, contact patterns, and
    large population movements.
  • Cho, T. (2003). Lexical stress, phrasal accent and prosodic boundaries in the realization of domain-initial stops in Dutch. In Proceedings of the 15th International Congress of Phonetic Sciences (ICPhs 2003) (pp. 2657-2660). Adelaide: Causal Productions.

    Abstract

    This study examines the effects of prosodic boundaries, lexical stress, and phrasal accent on the acoustic realization of stops (/t, d/) in Dutch, with special attention paid to language-specificity in the phonetics-prosody interface. The results obtained from various acoustic measures show systematic phonetic variations in the production of /t d/ as a function of prosodic position, which may be interpreted as being due to prosodicallyconditioned articulatory strengthening. Shorter VOTs were found for the voiceless stop /t/ in prosodically stronger locations (as opposed to longer VOTs in this position in English). The results suggest that prosodically-driven phonetic realization is bounded by a language-specific phonological feature system.
  • Cristia, A., Ganesh, S., Casillas, M., & Ganapathy, S. (2018). Talker diarization in the wild: The case of child-centered daylong audio-recordings. In Proceedings of Interspeech 2018 (pp. 2583-2587). doi:10.21437/Interspeech.2018-2078.

    Abstract

    Speaker diarization (answering 'who spoke when') is a widely researched subject within speech technology. Numerous experiments have been run on datasets built from broadcast news, meeting data, and call centers—the task sometimes appears close to being solved. Much less work has begun to tackle the hardest diarization task of all: spontaneous conversations in real-world settings. Such diarization would be particularly useful for studies of language acquisition, where researchers investigate the speech children produce and hear in their daily lives. In this paper, we study audio gathered with a recorder worn by small children as they went about their normal days. As a result, each child was exposed to different acoustic environments with a multitude of background noises and a varying number of adults and peers. The inconsistency of speech and noise within and across samples poses a challenging task for speaker diarization systems, which we tackled via retraining and data augmentation techniques. We further studied sources of structured variation across raw audio files, including the impact of speaker type distribution, proportion of speech from children, and child age on diarization performance. We discuss the extent to which these findings might generalize to other samples of speech in the wild.
  • Cutler, A., Murty, L., & Otake, T. (2003). Rhythmic similarity effects in non-native listening? In Proceedings of the 15th International Congress of Phonetic Sciences (PCPhS 2003) (pp. 329-332). Adelaide: Causal Productions.

    Abstract

    Listeners rely on native-language rhythm in segmenting speech; in different languages, stress-, syllable- or mora-based rhythm is exploited. This language-specificity affects listening to non- native speech, if native procedures are applied even though inefficient for the non-native language. However, speakers of two languages with similar rhythmic interpretation should segment their own and the other language similarly. This was observed to date only for related languages (English-Dutch; French-Spanish). We now report experiments in which Japanese listeners heard Telugu, a Dravidian language unrelated to Japanese, and Telugu listeners heard Japanese. In both cases detection of target sequences in speech was harder when target boundaries mismatched mora boundaries, exactly the pattern that Japanese listeners earlier exhibited with Japanese and other languages. These results suggest that Telugu and Japanese listeners use similar procedures in segmenting speech, and support the idea that languages fall into rhythmic classes, with aspects of phonological structure affecting listeners' speech segmentation.
  • Ip, M. H. K., & Cutler, A. (2018). Asymmetric efficiency of juncture perception in L1 and L2. In K. Klessa, J. Bachan, A. Wagner, M. Karpiński, & D. Śledziński (Eds.), Proceedings of Speech Prosody 2018 (pp. 289-296). Baixas, France: ISCA. doi:10.21437/SpeechProsody.2018-59.

    Abstract

    In two experiments, Mandarin listeners resolved potential syntactic ambiguities in spoken utterances in (a) their native language (L1) and (b) English which they had learned as a second language (L2). A new disambiguation task was used, requiring speeded responses to select the correct meaning for structurally ambiguous sentences. Importantly, the ambiguities used in the study are identical in Mandarin and in English, and production data show that prosodic disambiguation of this type of ambiguity is also realised very similarly in the two languages. The perceptual results here showed however that listeners’ response patterns differed for L1 and L2, although there was a significant increase in similarity between the two response patterns with increasing exposure to the L2. Thus identical ambiguity and comparable disambiguation patterns in L1 and L2 do not lead to immediate application of the appropriate L1 listening strategy to L2; instead, it appears that such a strategy may have to be learned anew for the L2.
  • Ip, M. H. K., & Cutler, A. (2018). Cue equivalence in prosodic entrainment for focus detection. In J. Epps, J. Wolfe, J. Smith, & C. Jones (Eds.), Proceedings of the 17th Australasian International Conference on Speech Science and Technology (pp. 153-156).

    Abstract

    Using a phoneme detection task, the present series of
    experiments examines whether listeners can entrain to
    different combinations of prosodic cues to predict where focus
    will fall in an utterance. The stimuli were recorded by four
    female native speakers of Australian English who happened to
    have used different prosodic cues to produce sentences with
    prosodic focus: a combination of duration cues, mean and
    maximum F0, F0 range, and longer pre-target interval before
    the focused word onset, only mean F0 cues, only pre-target
    interval, and only duration cues. Results revealed that listeners
    can entrain in almost every condition except for where
    duration was the only reliable cue. Our findings suggest that
    listeners are flexible in the cues they use for focus processing.
  • Cutler, A., Burchfield, L. A., & Antoniou, M. (2018). Factors affecting talker adaptation in a second language. In J. Epps, J. Wolfe, J. Smith, & C. Jones (Eds.), Proceedings of the 17th Australasian International Conference on Speech Science and Technology (pp. 33-36).

    Abstract

    Listeners adapt rapidly to previously unheard talkers by
    adjusting phoneme categories using lexical knowledge, in a
    process termed lexically-guided perceptual learning. Although
    this is firmly established for listening in the native language
    (L1), perceptual flexibility in second languages (L2) is as yet
    less well understood. We report two experiments examining L1
    and L2 perceptual learning, the first in Mandarin-English late
    bilinguals, the second in Australian learners of Mandarin. Both
    studies showed stronger learning in L1; in L2, however,
    learning appeared for the English-L1 group but not for the
    Mandarin-L1 group. Phonological mapping differences from
    the L1 to the L2 are suggested as the reason for this result.
  • Cutler, A. (1983). Semantics, syntax and sentence accent. In M. Van den Broecke, & A. Cohen (Eds.), Proceedings of the Tenth International Congress of Phonetic Sciences (pp. 85-91). Dordrecht: Foris.
  • Cutler, A., & Butterfield, S. (1986). The perceptual integrity of initial consonant clusters. In R. Lawrence (Ed.), Speech and Hearing: Proceedings of the Institute of Acoustics (pp. 31-36). Edinburgh: Institute of Acoustics.
  • Declerck, T., Cunningham, H., Saggion, H., Kuper, J., Reidsma, D., & Wittenburg, P. (2003). MUMIS - Advanced information extraction for multimedia indexing and searching digital media - Processing for multimedia interactive services. 4th European Workshop on Image Analysis for Multimedia Interactive Services (WIAMIS), 553-556.
  • Delgado, T., Ravignani, A., Verhoef, T., Thompson, B., Grossi, T., & Kirby, S. (2018). Cultural transmission of melodic and rhythmic universals: Four experiments and a model. In C. Cuskley, M. Flaherty, H. Little, L. McCrohon, A. Ravignani, & T. Verhoef (Eds.), Proceedings of the 12th International Conference on the Evolution of Language (EVOLANG XII) (pp. 89-91). Toruń, Poland: NCU Press. doi:10.12775/3991-1.019.
  • Dingemanse, M., Liesenfeld, A., & Woensdregt, M. (2022). Convergent cultural evolution of continuers (mhmm). In A. Ravignani, R. Asano, D. Valente, F. Ferretti, S. Hartmann, M. Hayashi, Y. Jadoul, M. Martins, Y. Oseki, E. D. Rodrigues, O. Vasileva, & S. Wacewicz (Eds.), The Evolution of Language: Proceedings of the Joint Conference on Language Evolution (JCoLE) (pp. 160-167). Nijmegen: Joint Conference on Language Evolution (JCoLE). doi:10.31234/osf.io/65c79.

    Abstract

    Continuers —words like mm, mmhm, uhum and the like— are among the most frequent types of responses in conversation. They play a key role in joint action coordination by showing positive evidence of understanding and scaffolding narrative delivery. Here we investigate the hypothesis that their functional importance along with their conversational ecology places selective pressures on their form and may lead to cross-linguistic similarities through convergent cultural evolution. We compare continuer tokens in linguistically diverse conversational corpora and find languages make available highly similar forms. We then approach the causal mechanism of convergent cultural evolution using exemplar modelling, simulating the process by which a combination of effort minimization and functional specialization may push continuers to a particular region of phonological possibility space. By combining comparative linguistics and computational modelling we shed new light on the question of how language structure is shaped by and for social interaction.
  • Dingemanse, M., & Liesenfeld, A. (2022). From text to talk: Harnessing conversational corpora for humane and diversity-aware language technology. In S. Muresan, P. Nakov, & A. Villavicencio (Eds.), Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (ACL 2022) (pp. 5614 -5633). Dublin, Ireland: Association for Computational Linguistics.

    Abstract

    Informal social interaction is the primordial home of human language. Linguistically diverse conversational corpora are an important and largely untapped resource for computational linguistics and language technology. Through the efforts of a worldwide language documentation movement, such corpora are increasingly becoming available. We show how interactional data from 63 languages (26 families) harbours insights about turn-taking, timing, sequential structure and social action, with implications for language technology, natural language understanding, and the design of conversational interfaces. Harnessing linguistically diverse conversational corpora will provide the empirical foundations for flexible, localizable, humane language technologies of the future.
  • Dona, L., & Schouwstra, M. (2022). The Role of Structural Priming, Semantics and Population Structure in Word Order Conventionalization: A Computational Model. In A. Ravignani, R. Asano, D. Valente, F. Ferretti, S. Hartmann, M. Hayashi, Y. Jadoul, M. Martins, Y. Oseki, E. D. Rodrigues, O. Vasileva, & S. Wacewicz (Eds.), The evolution of language: Proceedings of the Joint Conference on Language Evolution (JCoLE) (pp. 171-173). Nijmegen: Joint Conference on Language Evolution (JCoLE).
  • Drude, S. (2003). Advanced glossing: A language documentation format and its implementation with Shoebox. In Proceedings of the 2002 International Conference on Language Resources and Evaluation (LREC 2002). Paris: ELRA.

    Abstract

    This paper presents Advanced Glossing, a proposal for a general glossing format designed for language documentation, and a specific setup for the Shoebox-program that implements Advanced Glossing to a large extent. Advanced Glossing (AG) goes beyond the traditional Interlinear Morphemic Translation, keeping syntactic and morphological information apart from each other in separate glossing tables. AG provides specific lines for different kinds of annotation – phonetic, phonological, orthographical, prosodic, categorial, structural, relational, and semantic, and it allows for gradual and successive, incomplete, and partial filling in case that some information may be irrelevant, unknown or uncertain. The implementation of AG in Shoebox sets up several databases. Each documented text is represented as a file of syntactic glossings. The morphological glossings are kept in a separate database. As an additional feature interaction with lexical databases is possible. The implementation makes use of the interlinearizing automatism provided by Shoebox, thus obtaining the table format for the alignment of lines in cells, and for semi-automatic filling-in of information in glossing tables which has been extracted from databases
  • Drude, S. (2003). Digitizing and annotating texts and field recordings in the Awetí project. In Proceedings of the EMELD Language Digitization Project Conference 2003. Workshop on Digitizing and Annotating Text and Field Recordings, LSA Institute, Michigan State University, July 11th -13th.

    Abstract

    Digitizing and annotating texts and field recordings Given that several initiatives worldwide currently explore the new field of documentation of endangered languages, the E-MELD project proposes to survey and unite procedures, techniques and results in order to achieve its main goal, ''the formulation and promulgation of best practice in linguistic markup of texts and lexicons''. In this context, this year's workshop deals with the processing of recorded texts. I assume the most valuable contribution I could make to the workshop is to show the procedures and methods used in the Awetí Language Documentation Project. The procedures applied in the Awetí Project are not necessarily representative of all the projects in the DOBES program, and they may very well fall short in several respects of being best practice, but I hope they might provide a good and concrete starting point for comparison, criticism and further discussion. The procedures to be exposed include: * taping with digital devices, * digitizing (preliminarily in the field, later definitely by the TIDEL-team at the Max Planck Institute in Nijmegen), * segmenting and transcribing, using the transcriber computer program, * translating (on paper, or while transcribing), * adding more specific annotation, using the Shoebox program, * converting the annotation to the ELAN-format developed by the TIDEL-team, and doing annotation with ELAN. Focus will be on the different types of annotation. Especially, I will present, justify and discuss Advanced Glossing, a text annotation format developed by H.-H. Lieb and myself designed for language documentation. It will be shown how Advanced Glossing can be applied using the Shoebox program. The Shoebox setup used in the Awetí Project will be shown in greater detail, including lexical databases and semi-automatic interaction between different database types (jumping, interlinearization). ( Freie Universität Berlin and Museu Paraense Emílio Goeldi, with funding from the Volkswagen Foundation.)
  • Duarte, R., Uhlmann, M., Van den Broek, D., Fitz, H., Petersson, K. M., & Morrison, A. (2018). Encoding symbolic sequences with spiking neural reservoirs. In Proceedings of the 2018 International Joint Conference on Neural Networks (IJCNN). doi:10.1109/IJCNN.2018.8489114.

    Abstract

    Biologically inspired spiking networks are an important tool to study the nature of computation and cognition in neural systems. In this work, we investigate the representational capacity of spiking networks engaged in an identity mapping task. We compare two schemes for encoding symbolic input, one in which input is injected as a direct current and one where input is delivered as a spatio-temporal spike pattern. We test the ability of networks to discriminate their input as a function of the number of distinct input symbols. We also compare performance using either membrane potentials or filtered spike trains as state variable. Furthermore, we investigate how the circuit behavior depends on the balance between excitation and inhibition, and the degree of synchrony and regularity in its internal dynamics. Finally, we compare different linear methods of decoding population activity onto desired target labels. Overall, our results suggest that even this simple mapping task is strongly influenced by design choices on input encoding, state-variables, circuit characteristics and decoding methods, and these factors can interact in complex ways. This work highlights the importance of constraining computational network models of behavior by available neurobiological evidence.
  • Duffield, N., & Matsuo, A. (2003). Factoring out the parallelism effect in ellipsis: An interactional approach? In J. Chilar, A. Franklin, D. Keizer, & I. Kimbara (Eds.), Proceedings of the 39th Annual Meeting of the Chicago Linguistic Society (CLS) (pp. 591-603). Chicago: Chicago Linguistics Society.

    Abstract

    Traditionally, there have been three standard assumptions made about the Parallelism Effect on VP-ellipsis, namely that the effect is categorical, that it applies asymmetrically and that it is uniquely due to syntactic factors. Based on the results of a series of experiments involving online and offline tasks, it will be argued that the Parallelism Effect is instead noncategorical and interactional. The factors investigated include construction type, conceptual and morpho-syntactic recoverability, finiteness and anaphor type (to test VP-anaphora). The results show that parallelism is gradient rather than categorical, effects both VP-ellipsis and anaphora, and is influenced by both structural and non-structural factors.
  • Ergin, R., Senghas, A., Jackendoff, R., & Gleitman, L. (2018). Structural cues for symmetry, asymmetry, and non-symmetry in Central Taurus Sign Language. In C. Cuskley, M. Flaherty, H. Little, L. McCrohon, A. Ravignani, & T. Verhoef (Eds.), Proceedings of the 12th International Conference on the Evolution of Language (EVOLANG XII) (pp. 104-106). Toruń, Poland: NCU Press. doi:10.12775/3991-1.025.
  • Fletcher, J., Kidd, E., Stoakes, H., & Nordlinger, R. (2022). Prosodic phrasing, pitch range, and word order variation in Murrinhpatha. In R. Billington (Ed.), Proceedings of the 18th Australasian International Conference on Speech Science and Technology (pp. 201-205). Canberra: Australasian Speech Science and Technology Association.

    Abstract

    Like many Indigenous Australian languages, Murrinhpatha has flexible word order with no apparent configurational syntax. We analyzed an experimental corpus of Murrinhpatha utterances for associations between different thematic role orders, intonational phrasing patterns and pitch downtrends. We found that initial constituents (Agents or Patients) tend to carry the highest pitch targets (HiF0), followed by patterns of downstep and declination. Sentence-final verbs always have lower Hif0 values than either initial or medial Agents or Patients. Thematic role order does not influence intonational
    patterns, with the results suggesting that Murrinhpatha has positional prosody, although final nominals can disrupt global
    pitch downtrends regardless of thematic role.
  • Galke, L., Gerstenkorn, G., & Scherp, A. (2018). A case study of closed-domain response suggestion with limited training data. In M. Elloumi, M. Granitzer, A. Hameurlain, C. Seifert, B. Stein, A. Min Tjoa, & R. Wagner (Eds.), Database and Expert Systems Applications: DEXA 2018 International Workshops, BDMICS, BIOKDD, and TIR, Regensburg, Germany, September 3–6, 2018, Proceedings (pp. 218-229). Cham, Switzerland: Springer.

    Abstract

    We analyze the problem of response suggestion in a closed domain along a real-world scenario of a digital library. We present a text-processing pipeline to generate question-answer pairs from chat transcripts. On this limited amount of training data, we compare retrieval-based, conditioned-generation, and dedicated representation learning approaches for response suggestion. Our results show that retrieval-based methods that strive to find similar, known contexts are preferable over parametric approaches from the conditioned-generation family, when the training data is limited. We, however, identify a specific representation learning approach that is competitive to the retrieval-based approaches despite the training data limitation.
  • Galke, L., Mai, F., & Vagliano, I. (2018). Multi-modal adversarial autoencoders for recommendations of citations and subject labels. In T. Mitrovic, J. Zhang, L. Chen, & D. Chin (Eds.), UMAP '18: Proceedings of the 26th Conference on User Modeling, Adaptation and Personalization (pp. 197-205). New York: ACM. doi:10.1145/3209219.3209236.

    Abstract

    We present multi-modal adversarial autoencoders for recommendation and evaluate them on two different tasks: citation recommendation and subject label recommendation. We analyze the effects of adversarial regularization, sparsity, and different input modalities. By conducting 408 experiments, we show that adversarial regularization consistently improves the performance of autoencoders for recommendation. We demonstrate, however, that the two tasks differ in the semantics of item co-occurrence in the sense that item co-occurrence resembles relatedness in case of citations, yet implies diversity in case of subject labels. Our results reveal that supplying the partial item set as input is only helpful, when item co-occurrence resembles relatedness. When facing a new recommendation task it is therefore crucial to consider the semantics of item co-occurrence for the choice of an appropriate model.
  • Galke, L., & Scherp, A. (2022). Bag-of-words vs. graph vs. sequence in text classification: Questioning the necessity of text-graphs and the surprising strength of a wide MLP. In S. Muresan, P. Nakov, & A. Villavicencio (Eds.), Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (pp. 4038-4051). Dublin: Association for Computational Linguistics. doi:10.18653/v1/2022.acl-long.279.
  • Galke, L., Cuber, I., Meyer, C., Nölscher, H. F., Sonderecker, A., & Scherp, A. (2022). General cross-architecture distillation of pretrained language models into matrix embedding. In Proceedings of the IEEE Joint Conference on Neural Networks (IJCNN 2022), part of the IEEE World Congress on Computational Intelligence (WCCI 2022). doi:10.1109/IJCNN55064.2022.9892144.

    Abstract

    Large pretrained language models (PreLMs) are rev-olutionizing natural language processing across all benchmarks. However, their sheer size is prohibitive for small laboratories or for deployment on mobile devices. Approaches like pruning and distillation reduce the model size but typically retain the same model architecture. In contrast, we explore distilling PreLMs into a different, more efficient architecture, Continual Multiplication of Words (CMOW), which embeds each word as a matrix and uses matrix multiplication to encode sequences. We extend the CMOW architecture and its CMOW/CBOW-Hybrid variant with a bidirectional component for more expressive power, per-token representations for a general (task-agnostic) distillation during pretraining, and a two-sequence encoding scheme that facilitates downstream tasks on sentence pairs, such as sentence similarity and natural language inference. Our matrix-based bidirectional CMOW/CBOW-Hybrid model is competitive to DistilBERT on question similarity and recognizing textual entailment, but uses only half of the number of parameters and is three times faster in terms of inference speed. We match or exceed the scores of ELMo for all tasks of the GLUE benchmark except for the sentiment analysis task SST-2 and the linguistic acceptability task CoLA. However, compared to previous cross-architecture distillation approaches, we demonstrate a doubling of the scores on detecting linguistic acceptability. This shows that matrix-based embeddings can be used to distill large PreLM into competitive models and motivates further research in this direction.
  • Gamba, M., De Gregorio, C., Valente, D., Raimondi, T., Torti, V., Miaretsoa, L., Carugati, F., Friard, O., Giacoma, C., & Ravignani, A. (2022). Primate rhythmic categories analyzed on an individual basis. In A. Ravignani, R. Asano, D. Valente, F. Ferretti, S. Hartmann, M. Hayashi, Y. Jadoul, M. Martins, Y. Oseki, E. D. Rodrigues, O. Vasileva, & S. Wacewicz (Eds.), The evolution of language: Proceedings of the Joint Conference on Language Evolution (JCoLE) (pp. 229-236). Nijmegen: Joint Conference on Language Evolution (JCoLE).

    Abstract

    Rhythm is a fundamental feature characterizing communicative displays, and recent studies showed that primate songs encompass categorical rhythms falling on small integer ratios observed in humans. We individually assessed the presence and sexual dimorphism of rhythmic categories, analyzing songs emitted by 39 wild indris. Considering the intervals between the units given during each song, we extracted 13556 interval ratios and found three peaks (at around 0.33, 0.47, and 0.70). Two peaks indicated rhythmic categories corresponding to small integer ratios (1:1, 2:1). All individuals showed a peak at 0.70, and
    most showed those at 0.47 and 0.33. In addition, we found sex differences in the peak at 0.47 only, with males showing lower values than females. This work investigates the presence of individual rhythmic categories in a non-human species; further research may highlight the significance of rhythmicity and untie selective pressures that guided its evolution across species, including humans.
  • Hintz, F., Voeten, C. C., McQueen, J. M., & Meyer, A. S. (2022). Quantifying the relationships between linguistic experience, general cognitive skills and linguistic processing skills. In J. Culbertson, A. Perfors, H. Rabagliati, & V. Ramenzoni (Eds.), Proceedings of the 44th Annual Conference of the Cognitive Science Society (CogSci 2022) (pp. 2491-2496). Toronto, Canada: Cognitive Science Society.

    Abstract

    Humans differ greatly in their ability to use language. Contemporary psycholinguistic theories assume that individual differences in language skills arise from variability in linguistic experience and in general cognitive skills. While much previous research has tested the involvement of select verbal and non-verbal variables in select domains of linguistic processing, comprehensive characterizations of the relationships among the skills underlying language use are rare. We contribute to such a research program by re-analyzing a publicly available set of data from 112 young adults tested on 35 behavioral tests. The tests assessed nine key constructs reflecting linguistic processing skills, linguistic experience and general cognitive skills. Correlation and hierarchical clustering analyses of the test scores showed that most of the tests assumed to measure the same construct correlated moderately to strongly and largely clustered together. Furthermore, the results suggest important roles of processing speed in comprehension, and of linguistic experience in production.
  • Hoeksema, N., Hagoort, P., & Vernes, S. C. (2022). Piecing together the building blocks of the vocal learning bat brain. In A. Ravignani, R. Asano, D. Valente, F. Ferretti, S. Hartmann, M. Hayashi, Y. Jadoul, M. Martins, Y. Oseki, E. D. Rodrigues, O. Vasileva, & S. Wacewicz (Eds.), The evolution of language: Proceedings of the Joint Conference on Language Evolution (JCoLE) (pp. 294-296). Nijmegen: Joint Conference on Language Evolution (JCoLE).
  • Hopman, E., Thompson, B., Austerweil, J., & Lupyan, G. (2018). Predictors of L2 word learning accuracy: A big data investigation. In C. Kalish, M. Rau, J. Zhu, & T. T. Rogers (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (CogSci 2018) (pp. 513-518). Austin, TX: Cognitive Science Society.

    Abstract

    What makes some words harder to learn than others in a second language? Although some robust factors have been identified based on small scale experimental studies, many relevant factors are difficult to study in such experiments due to the amount of data necessary to test them. Here, we investigate what factors affect the ease of learning of a word in a second language using a large data set of users learning English as a second language through the Duolingo mobile app. In a regression analysis, we test and confirm the well-studied effect of cognate status on word learning accuracy. Furthermore, we find significant effects for both cross-linguistic semantic alignment and English semantic density, two novel predictors derived from large scale distributional models of lexical semantics. Finally, we provide data on several other psycholinguistically plausible word level predictors. We conclude with a discussion of the limits, benefits and future research potential of using big data for investigating second language learning.
  • Huettig, F., Kolinsky, R., & Lachmann, T. (Eds.). (2018). The effects of literacy on cognition and brain functioning [Special Issue]. Language, Cognition and Neuroscience, 33(3).
  • Isbilen, E., Frost, R. L. A., Monaghan, P., & Christiansen, M. (2018). Bridging artificial and natural language learning: Comparing processing- and reflection-based measures of learning. In C. Kalish, M. Rau, J. Zhu, & T. T. Rogers (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (CogSci 2018) (pp. 1856-1861). Austin, TX: Cognitive Science Society.

    Abstract

    A common assumption in the cognitive sciences is that artificial and natural language learning rely on shared mechanisms. However, attempts to bridge the two have yielded ambiguous results. We suggest that an empirical disconnect between the computations employed during learning and the methods employed at test may explain these mixed results. Further, we propose statistically-based chunking as a potential computational link between artificial and natural language learning. We compare the acquisition of non-adjacent dependencies to that of natural language structure using two types of tasks: reflection-based 2AFC measures, and processing-based recall measures, the latter being more computationally analogous to the processes used during language acquisition. Our results demonstrate that task-type significantly influences the correlations observed between artificial and natural language acquisition, with reflection-based and processing-based measures correlating within – but not across – task-type. These findings have fundamental implications for artificial-to-natural language comparisons, both methodologically and theoretically.
  • Janse, E. (2003). Word perception in natural-fast and artificially time-compressed speech. In M. SolÉ, D. Recasens, & J. Romero (Eds.), Proceedings of the 15th International Congress of the Phonetic Sciences (pp. 3001-3004).
  • Janssen, R., Moisik, S. R., & Dediu, D. (2018). Agent model reveals the influence of vocal tract anatomy on speech during ontogeny and glossogeny. In C. Cuskley, M. Flaherty, H. Little, L. McCrohon, A. Ravignani, & T. Verhoef (Eds.), Proceedings of the 12th International Conference on the Evolution of Language (EVOLANG XII) (pp. 171-174). Toruń, Poland: NCU Press. doi:10.12775/3991-1.042.
  • Johnson, E. K. (2003). Speaker intent influences infants' segmentation of potentially ambiguous utterances. In Proceedings of the 15th International Congress of Phonetic Sciences (PCPhS 2003) (pp. 1995-1998). Adelaide: Causal Productions.
  • Kan, U., Gökgöz, K., Sumer, B., Tamyürek, E., & Özyürek, A. (2022). Emergence of negation in a Turkish homesign system: Insights from the family context. In A. Ravignani, R. Asano, D. Valente, F. Ferretti, S. Hartmann, M. Hayashi, Y. Jadoul, M. Martins, Y. Oseki, E. D. Rodrigues, O. Vasileva, & S. Wacewicz (Eds.), The evolution of language: Proceedings of the Joint Conference on Language Evolution (JCoLE) (pp. 387-389). Nijmegen: Joint Conference on Language Evolution (JCoLE).
  • Kanero, J., Franko, I., Oranç, C., Uluşahin, O., Koskulu, S., Adigüzel, Z., Küntay, A. C., & Göksun, T. (2018). Who can benefit from robots? Effects of individual differences in robot-assisted language learning. In Proceedings of the 8th International Conference on Development and Learning and Epigenetic Robotics (ICDL-EpiRob) (pp. 212-217). Piscataway, NJ, USA: IEEE.

    Abstract

    It has been suggested that some individuals may benefit more from social robots than do others. Using second
    language (L2) as an example, the present study examined how individual differences in attitudes toward robots and personality
    traits may be related to learning outcomes. Preliminary results with 24 Turkish-speaking adults suggest that negative attitudes
    toward robots, more specifically thoughts and anxiety about the negative social impact that robots may have on the society,
    predicted how well adults learned L2 words from a social robot. The possible implications of the findings as well as future directions are also discussed
  • Kempen, G., & Harbusch, K. (2003). A corpus study into word order variation in German subordinate clauses: Animacy affects linearization independently of function assignment. In Proceedings of AMLaP 2003 (pp. 153-154). Glasgow: Glasgow University.
  • Klein, W., & Franceschini, R. (Eds.). (2003). Einfache Sprache [Special Issue]. Zeitschrift für Literaturwissenschaft und Linguistik, 131.
  • Klein, W. (Ed.). (1983). Intonation [Special Issue]. Zeitschrift für Literaturwissenschaft und Linguistik, (49).
  • Klein, W. (Ed.). (1979). Sprache und Kontext [Special Issue]. Zeitschrift für Literaturwissenschaft und Linguistik, (33).
  • Klein, W. (Ed.). (1986). Sprachverfall [Special Issue]. Zeitschrift für Literaturwissenschaft und Linguistik, (62).
  • Kohatsu, T., Akamine, S., Sato, M., & Niikuni, K. (2022). Individual differences in empathy affect perspective adoption in language comprehension. In Proceedings of the 39th Annual Meeting of Japanese Cognitive Science Society (pp. 652-656). Tokyo: Japanese Cognitive Science Society.
  • Kuzla, C. (2003). Prosodically-conditioned variation in the realization of domain-final stops and voicing assimilation of domain-initial fricatives in German. In Proceedings of the 15th International Congress of Phonetic Sciences (ICPhS 2003) (pp. 2829-2832). Adelaide: Causal Productions.
  • De Lange, F. P., Hagoort, P., & Toni, I. (2003). Differential fronto-parietal contributions to visual and motor imagery. NeuroImage, 19(2), e2094-e2095.

    Abstract

    Mental imagery is a cognitive process crucial to human reasoning. Numerous studies have characterized specific
    instances of this cognitive ability, as evoked by visual imagery (VI) or motor imagery (MI) tasks. However, it
    remains unclear which neural resources are shared between VI and MI, and which are exclusively related to MI.
    To address this issue, we have used fMRI to measure human brain activity during performance of VI and MI
    tasks. Crucially, we have modulated the imagery process by manipulating the degree of mental rotation necessary
    to solve the tasks. We focused our analysis on changes in neural signal as a function of the degree of mental
    rotation in each task.
  • Lattenkamp, E. Z., Vernes, S. C., & Wiegrebe, L. (2018). Mammalian models for the study of vocal learning: A new paradigm in bats. In C. Cuskley, M. Flaherty, H. Little, L. McCrohon, A. Ravignani, & T. Verhoef (Eds.), Proceedings of the 12th International Conference on the Evolution of Language (EVOLANG XII) (pp. 235-237). Toruń, Poland: NCU Press. doi:10.12775/3991-1.056.
  • Lauscher, A., Eckert, K., Galke, L., Scherp, A., Rizvi, S. T. R., Ahmed, S., Dengel, A., Zumstein, P., & Klein, A. (2018). Linked open citation database: Enabling libraries to contribute to an open and interconnected citation graph. In J. Chen, M. A. Gonçalves, J. M. Allen, E. A. Fox, M.-Y. Kan, & V. Petras (Eds.), JCDL '18: Proceedings of the 18th ACM/IEEE on Joint Conference on Digital Libraries (pp. 109-118). New York: ACM. doi:10.1145/3197026.3197050.

    Abstract

    Citations play a crucial role in the scientific discourse, in information retrieval, and in bibliometrics. Many initiatives are currently promoting the idea of having free and open citation data. Creation of citation data, however, is not part of the cataloging workflow in libraries nowadays.
    In this paper, we present our project Linked Open Citation Database, in which we design distributed processes and a system infrastructure based on linked data technology. The goal is to show that efficiently cataloging citations in libraries using a semi-automatic approach is possible. We specifically describe the current state of the workflow and its implementation. We show that we could significantly improve the automatic reference extraction that is crucial for the subsequent data curation. We further give insights on the curation and linking process and provide evaluation results that not only direct the further development of the project, but also allow us to discuss its overall feasibility.
  • Lefever, E., Hendrickx, I., Croijmans, I., Van den Bosch, A., & Majid, A. (2018). Discovering the language of wine reviews: A text mining account. In N. Calzolari, K. Choukri, C. Cieri, T. Declerck, S. Goggi, K. Hasida, H. Isahara, B. Maegaard, J. Mariani, H. Mazo, A. Moreno, J. Odijk, S. Piperidis, & T. Tokunaga (Eds.), Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018) (pp. 3297-3302). Paris: LREC.

    Abstract

    It is widely held that smells and flavors are impossible to put into words. In this paper we test this claim by seeking predictive patterns in wine reviews, which ostensibly aim to provide guides to perceptual content. Wine reviews have previously been critiqued as random and meaningless. We collected an English corpus of wine reviews with their structured metadata, and applied machine learning techniques to automatically predict the wine's color, grape variety, and country of origin. To train the three supervised classifiers, three different information sources were incorporated: lexical bag-of-words features, domain-specific terminology features, and semantic word embedding features. In addition, using regression analysis we investigated basic review properties, i.e., review length, average word length, and their relationship to the scalar values of price and review score. Our results show that wine experts do share a common vocabulary to describe wines and they use this in a consistent way, which makes it possible to automatically predict wine characteristics based on the review text alone. This means that odors and flavors may be more expressible in language than typically acknowledged.
  • Levelt, C. C., Fikkert, P., & Schiller, N. O. (2003). Metrical priming in speech production. In Proceedings of the 15th International Congress of Phonetic Sciences (ICPhS 2003) (pp. 2481-2485). Adelaide: Causal Productions.

    Abstract

    In this paper we report on four experiments in which we attempted to prime the stress position of Dutch bisyllabic target nouns. These nouns, picture names, had stress on either the first or the second syllable. Auditory prime words had either the same stress as the target or a different stress (e.g., WORtel – MOtor vs. koSTUUM – MOtor; capital letters indicate stressed syllables in prime – target pairs). Furthermore, half of the prime words were semantically related, the other half were unrelated. In none of the experiments a stress priming effect was found. This could mean that stress is not stored in the lexicon. An additional finding was that targets with initial stress had a faster response than targets with a final stress. We hypothesize that bisyllabic words with final stress take longer to be encoded because this stress pattern is irregular with respect to the lexical distribution of bisyllabic stress patterns, even though it can be regular in terms of the metrical stress rules of Dutch.
  • Levelt, W. J. M. (1983). The speaker's organization of discourse. In Proceedings of the XIIIth International Congress of Linguists (pp. 278-290).
  • Levinson, S. C. (1979). Pragmatics and social deixis: Reclaiming the notion of conventional implicature. In C. Chiarello (Ed.), Proceedings of the Fifth Annual Meeting of the Berkeley Linguistics Society (pp. 206-223).
  • Liesenfeld, A., & Dingemanse, M. (2022). Bottom-up discovery of structure and variation in response tokens (‘backchannels’) across diverse languages. In Proceedings of Interspeech 2022 (pp. 1126-1130).

    Abstract

    Response tokens (also known as backchannels, continuers, or feedback) are a frequent feature of human interaction, where they serve to display understanding and streamline turn-taking. We propose a bottom-up method to study responsive behaviour across 16 languages (8 language families). We use sequential context and recurrence of turns formats to identify candidate response tokens in a language-agnostic way across diverse conversational corpora. We then use UMAP clustering directly on speech signals to represent structure and variation. We find that (i) written orthographic annotations underrepresent the attested variation, (ii) distinctions between formats can be gradient rather than discrete, (iii) most languages appear to make available a broad distinction between a minimal nasal format `mm' and a fuller `yeah’-like format. Charting this aspect of human interaction contributes to our understanding of interactional infrastructure across languages and can inform the design of speech technologies.
  • Liesenfeld, A., & Dingemanse, M. (2022). Building and curating conversational corpora for diversity-aware language science and technology. In F. Béchet, P. Blache, K. Choukri, C. Cieri, T. DeClerck, S. Goggi, H. Isahara, B. Maegaard, J. Mariani, H. Mazo, & J. Odijk (Eds.), Proceedings of the 13th Language Resources and Evaluation Conference (LREC 2022) (pp. 1178-1192). Marseille, France: European Language Resources Association.

    Abstract

    We present an analysis pipeline and best practice guidelines for building and curating corpora of everyday conversation in diverse languages. Surveying language documentation corpora and other resources that cover 67 languages and varieties from 28 phyla, we describe the compilation and curation process, specify minimal properties of a unified format for interactional data, and develop methods for quality control that take into account turn-taking and timing. Two case studies show the broad utility of conversational data for (i) charting human interactional infrastructure and (ii) tracing challenges and opportunities for current ASR solutions. Linguistically diverse conversational corpora can provide new insights for the language sciences and stronger empirical foundations for language technology.
  • Lopopolo, A., Frank, S. L., Van den Bosch, A., Nijhof, A., & Willems, R. M. (2018). The Narrative Brain Dataset (NBD), an fMRI dataset for the study of natural language processing in the brain. In B. Devereux, E. Shutova, & C.-R. Huang (Eds.), Proceedings of LREC 2018 Workshop "Linguistic and Neuro-Cognitive Resources (LiNCR) (pp. 8-11). Paris: LREC.

    Abstract

    We present the Narrative Brain Dataset, an fMRI dataset that was collected during spoken presentation of short excerpts of three
    stories in Dutch. Together with the brain imaging data, the dataset contains the written versions of the stimulation texts. The texts are
    accompanied with stochastic (perplexity and entropy) and semantic computational linguistic measures. The richness and unconstrained
    nature of the data allows the study of language processing in the brain in a more naturalistic setting than is common for fMRI studies.
    We hope that by making NBD available we serve the double purpose of providing useful neural data to researchers interested in natural
    language processing in the brain and to further stimulate data sharing in the field of neuroscience of language.
  • Lupyan, G., Wendorf, A., Berscia, L. M., & Paul, J. (2018). Core knowledge or language-augmented cognition? The case of geometric reasoning. In C. Cuskley, M. Flaherty, H. Little, L. McCrohon, A. Ravignani, & T. Verhoef (Eds.), Proceedings of the 12th International Conference on the Evolution of Language (EVOLANG XII) (pp. 252-254). Toruń, Poland: NCU Press. doi:10.12775/3991-1.062.
  • Mai, F., Galke, L., & Scherp, A. (2018). Using deep learning for title-based semantic subject indexing to reach competitive performance to full-text. In J. Chen, M. A. Gonçalves, J. M. Allen, E. A. Fox, M.-Y. Kan, & V. Petras (Eds.), JCDL '18: Proceedings of the 18th ACM/IEEE on Joint Conference on Digital Libraries (pp. 169-178). New York: ACM.

    Abstract

    For (semi-)automated subject indexing systems in digital libraries, it is often more practical to use metadata such as the title of a publication instead of the full-text or the abstract. Therefore, it is desirable to have good text mining and text classification algorithms that operate well already on the title of a publication. So far, the classification performance on titles is not competitive with the performance on the full-texts if the same number of training samples is used for training. However, it is much easier to obtain title data in large quantities and to use it for training than full-text data. In this paper, we investigate the question how models obtained from training on increasing amounts of title training data compare to models from training on a constant number of full-texts. We evaluate this question on a large-scale dataset from the medical domain (PubMed) and from economics (EconBiz). In these datasets, the titles and annotations of millions of publications are available, and they outnumber the available full-texts by a factor of 20 and 15, respectively. To exploit these large amounts of data to their full potential, we develop three strong deep learning classifiers and evaluate their performance on the two datasets. The results are promising. On the EconBiz dataset, all three classifiers outperform their full-text counterparts by a large margin. The best title-based classifier outperforms the best full-text method by 9.4%. On the PubMed dataset, the best title-based method almost reaches the performance of the best full-text classifier, with a difference of only 2.9%.
  • McQueen, J. M., & Cho, T. (2003). The use of domain-initial strengthening in segmentation of continuous English speech. In Proceedings of the 15th International Congress of Phonetic Sciences (ICPhS 2003) (pp. 2993-2996). Adelaide: Causal Productions.
  • Meeuwissen, M., Roelofs, A., & Levelt, W. J. M. (2003). Naming analog clocks conceptually facilitates naming digital clocks. In Proceedings of XIII Conference of the European Society of Cognitive Psychology (ESCOP 2003) (pp. 271-271).
  • Merkx, D., Frank, S. L., & Ernestus, M. (2022). Seeing the advantage: Visually grounding word embeddings to better capture human semantic knowledge. In E. Chersoni, N. Hollenstein, C. Jacobs, Y. Oseki, L. Prévot, & E. Santus (Eds.), Proceedings of the Workshop on Cognitive Modeling and Computational Linguistics (CMCL 2022) (pp. 1-11). Stroudsburg, PA, USA: Association for Computational Linguistics (ACL).

    Abstract

    Distributional semantic models capture word-level meaning that is useful in many natural language processing tasks and have even been shown to capture cognitive aspects of word meaning. The majority of these models are purely text based, even though the human sensory experience is much richer. In this paper we create visually grounded word embeddings by combining English text and images and compare them to popular text-based methods, to see if visual information allows our model to better capture cognitive aspects of word meaning. Our analysis shows that visually grounded embedding similarities are more predictive of the human reaction times in a large priming experiment than the purely text-based embeddings. The visually grounded embeddings also correlate well with human word similarity ratings.Importantly, in both experiments we show that he grounded embeddings account for a unique portion of explained variance, even when we include text-based embeddings trained on huge corpora. This shows that visual grounding allows our model to capture information that cannot be extracted using text as the only source of information.
  • Merkx, D., & Scharenborg, O. (2018). Articulatory feature classification using convolutional neural networks. In Proceedings of Interspeech 2018 (pp. 2142-2146). doi:10.21437/Interspeech.2018-2275.

    Abstract

    The ultimate goal of our research is to improve an existing speech-based computational model of human speech recognition on the task of simulating the role of fine-grained phonetic information in human speech processing. As part of this work we are investigating articulatory feature classifiers that are able to create reliable and accurate transcriptions of the articulatory behaviour encoded in the acoustic speech signal. Articulatory feature (AF) modelling of speech has received a considerable amount of attention in automatic speech recognition research. Different approaches have been used to build AF classifiers, most notably multi-layer perceptrons. Recently, deep neural networks have been applied to the task of AF classification. This paper aims to improve AF classification by investigating two different approaches: 1) investigating the usefulness of a deep Convolutional neural network (CNN) for AF classification; 2) integrating the Mel filtering operation into the CNN architecture. The results showed a remarkable improvement in classification accuracy of the CNNs over state-of-the-art AF classification results for Dutch, most notably in the minority classes. Integrating the Mel filtering operation into the CNN architecture did not further improve classification performance.
  • Micklos, A., Macuch Silva, V., & Fay, N. (2018). The prevalence of repair in studies of language evolution. In C. Cuskley, M. Flaherty, H. Little, L. McCrohon, A. Ravignani, & T. Verhoef (Eds.), Proceedings of the 12th International Conference on the Evolution of Language (EVOLANG XII) (pp. 316-318). Toruń, Poland: NCU Press. doi:10.12775/3991-1.075.
  • Mishra, C., & Skantze, G. (2022). Knowing where to look: A planning-based architecture to automate the gaze behavior of social robots. In Proceedings of the 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN) (pp. 1201-1208). doi:10.1109/RO-MAN53752.2022.9900740.

    Abstract

    Gaze cues play an important role in human communication and are used to coordinate turn-taking and joint attention, as well as to regulate intimacy. In order to have fluent conversations with people, social robots need to exhibit humanlike gaze behavior. Previous Gaze Control Systems (GCS) in HRI have automated robot gaze using data-driven or heuristic approaches. However, these systems tend to be mainly reactive in nature. Planning the robot gaze ahead of time could help in achieving more realistic gaze behavior and better eye-head coordination. In this paper, we propose and implement a novel planning-based GCS. We evaluate our system in a comparative within-subjects user study (N=26) between a reactive system and our proposed system. The results show that the users preferred the proposed system and that it was significantly more interpretable and better at regulating intimacy.
  • Moscoso del Prado Martín, F., & Baayen, R. H. (2003). Using the structure found in time: Building real-scale orthographic and phonetic representations by accumulation of expectations. In H. Bowman, & C. Labiouse (Eds.), Connectionist Models of Cognition, Perception and Emotion: Proceedings of the Eighth Neural Computation and Psychology Workshop (pp. 263-272). Singapore: World Scientific.
  • Mulder, K., Ten Bosch, L., & Boves, L. (2018). Analyzing EEG Signals in Auditory Speech Comprehension Using Temporal Response Functions and Generalized Additive Models. In Proceedings of Interspeech 2018 (pp. 1452-1456). doi:10.21437/Interspeech.2018-1676.

    Abstract

    Analyzing EEG signals recorded while participants are listening to continuous speech with the purpose of testing linguistic hypotheses is complicated by the fact that the signals simultaneously reflect exogenous acoustic excitation and endogenous linguistic processing. This makes it difficult to trace subtle differences that occur in mid-sentence position. We apply an analysis based on multivariate temporal response functions to uncover subtle mid-sentence effects. This approach is based on a per-stimulus estimate of the response of the neural system to speech input. Analyzing EEG signals predicted on the basis of the response functions might then bring to light conditionspecific differences in the filtered signals. We validate this approach by means of an analysis of EEG signals recorded with isolated word stimuli. Then, we apply the validated method to the analysis of the responses to the same words in the middle of meaningful sentences.
  • Oostdijk, N., & Broeder, D. (2003). The Spoken Dutch Corpus and its exploitation environment. In A. Abeille, S. Hansen-Schirra, & H. Uszkoreit (Eds.), Proceedings of the 4th International Workshop on linguistically interpreted corpora (LINC-03) (pp. 93-101).
  • Ouni, S., Cohen, M. M., Young, K., & Jesse, A. (2003). Internationalization of a talking head. In M. Sole, D. Recasens, & J. Romero (Eds.), Proceedings of 15th International Congress of Phonetics Sciences (pp. 2569-2572). Barcelona: Casual Productions.

    Abstract

    In this paper we describe a general scheme for internationalization of our talking head, Baldi, to speak other languages. We describe the modular structure of the auditory/visual synthesis software. As an example, we have created a synthetic Arabic talker, which is evaluated using a noisy word recognition task comparing this talker with a natural one.
  • Räsänen, O., Seshadri, S., & Casillas, M. (2018). Comparison of syllabification algorithms and training strategies for robust word count estimation across different languages and recording conditions. In Proceedings of Interspeech 2018 (pp. 1200-1204). doi:10.21437/Interspeech.2018-1047.

    Abstract

    Word count estimation (WCE) from audio recordings has a number of applications, including quantifying the amount of speech that language-learning infants hear in their natural environments, as captured by daylong recordings made with devices worn by infants. To be applicable in a wide range of scenarios and also low-resource domains, WCE tools should be extremely robust against varying signal conditions and require minimal access to labeled training data in the target domain. For this purpose, earlier work has used automatic syllabification of speech, followed by a least-squares-mapping of syllables to word counts. This paper compares a number of previously proposed syllabifiers in the WCE task, including a supervised bi-directional long short-term memory (BLSTM) network that is trained on a language for which high quality syllable annotations are available (a “high resource language”), and reports how the alternative methods compare on different languages and signal conditions. We also explore additive noise and varying-channel data augmentation strategies for BLSTM training, and show how they improve performance in both matching and mismatching languages. Intriguingly, we also find that even though the BLSTM works on languages beyond its training data, the unsupervised algorithms can still outperform it in challenging signal conditions on novel languages.
  • Ravignani, A., Garcia, M., Gross, S., de Reus, K., Hoeksema, N., Rubio-Garcia, A., & de Boer, B. (2018). Pinnipeds have something to say about speech and rhythm. In C. Cuskley, M. Flaherty, H. Little, L. McCrohon, A. Ravignani, & T. Verhoef (Eds.), Proceedings of the 12th International Conference on the Evolution of Language (EVOLANG XII) (pp. 399-401). Toruń, Poland: NCU Press. doi:10.12775/3991-1.095.
  • Raviv, L., Meyer, A. S., & Lev-Ari, S. (2018). The role of community size in the emergence of linguistic structure. In C. Cuskley, M. Flaherty, H. Little, L. McCrohon, A. Ravignani, & T. Verhoef (Eds.), Proceedings of the 12th International Conference on the Evolution of Language (EVOLANG XII) (pp. 402-404). Toruń, Poland: NCU Press. doi:10.12775/3991-1.096.
  • Raviv, L., Jacobson, S. L., Plotnik, J. M., Bowman, J., Lynch, V., & Benítez-Burraco, A. (2022). Elephants as a new animal model for studying the evolution of language as a result of self-domestication. In A. Ravignani, R. Asano, D. Valente, F. Ferretti, S. Hartmann, M. Hayashi, Y. Jadoul, M. Martins, Y. Oseki, E. D. Rodrigues, O. Vasileva, & S. Wacewicz (Eds.), The evolution of language: Proceedings of the Joint Conference on Language Evolution (JCoLE) (pp. 606-608). Nijmegen: Joint Conference on Language Evolution (JCoLE).
  • de Reus, K., Carlson, D., Lowry, A., Gross, S., Garcia, M., Rubio-García, A., Salazar-Casals, A., & Ravignani, A. (2022). Body size predicts vocal tract size in a mammalian vocal learner. In A. Ravignani, R. Asano, D. Valente, F. Ferretti, S. Hartmann, M. Hayashi, Y. Jadoul, M. Martins, Y. Oseki, E. D. Rodrigues, O. Vasileva, & S. Wacewicz (Eds.), The evolution of language: Proceedings of the Joint Conference on Language Evolution (JCoLE) (pp. 154-156). Nijmegen: Joint Conference on Language Evolution (JCoLE).
  • Rubio-Fernández, P., & Jara-Ettinger, J. (2018). Joint inferences of speakers’ beliefs and referents based on how they speak. In C. Kalish, M. Rau, J. Zhu, & T. T. Rogers (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (CogSci 2018) (pp. 991-996). Austin, TX: Cognitive Science Society.

    Abstract

    For almost two decades, the poor performance observed with the so-called Director task has been interpreted as evidence of limited use of Theory of Mind in communication. Here we propose a probabilistic model of common ground in referential communication that derives three inferences from an utterance: what the speaker is talking about in a visual context, what she knows about the context, and what referential expressions she prefers. We tested our model by comparing its inferences with those made by human participants and found that it closely mirrors their judgments, whereas an alternative model compromising the hearer’s expectations of cooperativeness and efficiency reveals a worse fit to the human data. Rather than assuming that common ground is fixed in a given exchange and may or may not constrain reference resolution, we show how common ground can be inferred as part of the process of reference assignment.
  • Rubio-Fernández, P., Breheny, R., & Lee, M. W. (2003). Context-independent information in concepts: An investigation of the notion of ‘core features’. In Proceedings of the 25th Annual Conference of the Cognitive Science Society (CogSci 2003). Austin, TX: Cognitive Science Society.
  • Saleh, A., Beck, T., Galke, L., & Scherp, A. (2018). Performance comparison of ad-hoc retrieval models over full-text vs. titles of documents. In M. Dobreva, A. Hinze, & M. Žumer (Eds.), Maturity and Innovation in Digital Libraries: 20th International Conference on Asia-Pacific Digital Libraries, ICADL 2018, Hamilton, New Zealand, November 19-22, 2018, Proceedings (pp. 290-303). Cham, Switzerland: Springer.

    Abstract

    While there are many studies on information retrieval models using full-text, there are presently no comparison studies of full-text retrieval vs. retrieval only over the titles of documents. On the one hand, the full-text of documents like scientific papers is not always available due to, e.g., copyright policies of academic publishers. On the other hand, conducting a search based on titles alone has strong limitations. Titles are short and therefore may not contain enough information to yield satisfactory search results. In this paper, we compare different retrieval models regarding their search performance on the full-text vs. only titles of documents. We use different datasets, including the three digital library datasets: EconBiz, IREON, and PubMed. The results show that it is possible to build effective title-based retrieval models that provide competitive results comparable to full-text retrieval. The difference between the average evaluation results of the best title-based retrieval models is only 3% less than those of the best full-text-based retrieval models.
  • Scharenborg, O., & Merkx, D. (2018). The role of articulatory feature representation quality in a computational model of human spoken-word recognition. In Proceedings of the Machine Learning in Speech and Language Processing Workshop (MLSLP 2018).

    Abstract

    Fine-Tracker is a speech-based model of human speech
    recognition. While previous work has shown that Fine-Tracker
    is successful at modelling aspects of human spoken-word
    recognition, its speech recognition performance is not
    comparable to that of human performance, possibly due to
    suboptimal intermediate articulatory feature (AF)
    representations. This study investigates the effect of improved
    AF representations, obtained using a state-of-the-art deep
    convolutional network, on Fine-Tracker’s simulation and
    recognition performance: Although the improved AF quality
    resulted in improved speech recognition; it, surprisingly, did
    not lead to an improvement in Fine-Tracker’s simulation power.
  • Scharenborg, O., McQueen, J. M., Ten Bosch, L., & Norris, D. (2003). Modelling human speech recognition using automatic speech recognition paradigms in SpeM. In Proceedings of Eurospeech 2003 (pp. 2097-2100). Adelaide: Causal Productions.

    Abstract

    We have recently developed a new model of human speech recognition, based on automatic speech recognition techniques [1]. The present paper has two goals. First, we show that the new model performs well in the recognition of lexically ambiguous input. These demonstrations suggest that the model is able to operate in the same optimal way as human listeners. Second, we discuss how to relate the behaviour of a recogniser, designed to discover the optimum path through a word lattice, to data from human listening experiments. We argue that this requires a metric that combines both path-based and word-based measures of recognition performance. The combined metric varies continuously as the input speech signal unfolds over time.
  • Scharenborg, O., ten Bosch, L., & Boves, L. (2003). Recognising 'real-life' speech with SpeM: A speech-based computational model of human speech recognition. In Eurospeech 2003 (pp. 2285-2288).

    Abstract

    In this paper, we present a novel computational model of human speech recognition – called SpeM – based on the theory underlying Shortlist. We will show that SpeM, in combination with an automatic phone recogniser (APR), is able to simulate the human speech recognition process from the acoustic signal to the ultimate recognition of words. This joint model takes an acoustic speech file as input and calculates the activation flows of candidate words on the basis of the degree of fit of the candidate words with the input. Experiments showed that SpeM outperforms Shortlist on the recognition of ‘real-life’ input. Furthermore, SpeM performs only slightly worse than an off-the-shelf full-blown automatic speech recogniser in which all words are equally probable, while it provides a transparent computationally elegant paradigm for modelling word activations in human word recognition.
  • Schiller, N. O. (2003). Metrical stress in speech production: A time course study. In Proceedings of the 15th International Congress of Phonetic Sciences (ICPhS 2003) (pp. 451-454). Adelaide: Causal Productions.

    Abstract

    This study investigated the encoding of metrical information during speech production in Dutch. In Experiment 1, participants were asked to judge whether bisyllabic picture names had initial or final stress. Results showed significantly faster decision times for initially stressed targets (e.g., LEpel 'spoon') than for targets with final stress (e.g., liBEL 'dragon fly'; capital letters indicate stressed syllables) and revealed that the monitoring latencies are not a function of the picture naming or object recognition latencies to the same pictures. Experiments 2 and 3 replicated the outcome of the first experiment with bi- and trisyllabic picture names. These results demonstrate that metrical information of words is encoded rightward incrementally during phonological encoding in speech production. The results of these experiments are in line with Levelt's model of phonological encoding.
  • Scholman, M., Tianai, D., Yung, F., & Demberg, V. (2022). DiscoGeM: A crowdsourced corpus of genre-mixed implicit discourse relations. In N. Calzolari, F. Béchet, P. Blache, K. Choukri, C. Cieri, T. DeClerck, S. Goggi, H. Isahara, B. Maegaard, J. Mariani, H. Mazo, J. Odijk, & S. Piperidis (Eds.), Proceedings of the 13th Language Resources and Evaluation Conference (LREC 2022) (pp. 3281-3290). Marseille, France: European Language Resources Association.

    Abstract

    We present DiscoGeM, a crowdsourced corpus of 6,505 implicit discourse relations from three genres: political speech,
    literature, and encyclopedic texts. Each instance was annotated by 10 crowd workers. Various label aggregation methods
    were explored to evaluate how to obtain a label that best captures the meaning inferred by the crowd annotators. The results
    show that a significant proportion of discourse relations in DiscoGeM are ambiguous and can express multiple relation senses.
    Probability distribution labels better capture these interpretations than single labels. Further, the results emphasize that text
    genre crucially affects the distribution of discourse relations, suggesting that genre should be included as a factor in automatic
    relation classification. We make available the newly created DiscoGeM corpus, as well as the dataset with all annotator-level
    labels. Both the corpus and the dataset can facilitate a multitude of applications and research purposes, for example to
    function as training data to improve the performance of automatic discourse relation parsers, as well as facilitate research into
    non-connective signals of discourse relations.
  • Seidl, A., & Johnson, E. K. (2003). Position and vowel quality effects in infant's segmentation of vowel-initial words. In Proceedings of the 15th International Congress of Phonetic Sciences (ICPhS 2003) (pp. 2233-2236). Adelaide: Causal Productions.
  • Severijnen, G. G., Bosker, H. R., & McQueen, J. M. (2022). Acoustic correlates of Dutch lexical stress re-examined: Spectral tilt is not always more reliable than intensity. In S. Frota, M. Cruz, & M. Vigário (Eds.), Proceedings of Speech Prosody 2022 (pp. 278-282). doi:10.21437/SpeechProsody.2022-57.

    Abstract

    The present study examined two acoustic cues in the production
    of lexical stress in Dutch: spectral tilt and overall intensity.
    Sluijter and Van Heuven (1996) reported that spectral tilt is a
    more reliable cue to stress than intensity. However, that study
    included only a small number of talkers (10) and only syllables
    with the vowels /aː/ and /ɔ/.
    The present study re-examined this issue in a larger and
    more variable dataset. We recorded 38 native speakers of Dutch
    (20 females) producing 744 tokens of Dutch segmentally
    overlapping words (e.g., VOORnaam vs. voorNAAM, “first
    name” vs. “respectable”), targeting 10 different vowels, in
    variable sentence contexts. For each syllable, we measured
    overall intensity and spectral tilt following Sluijter and Van
    Heuven (1996).
    Results from Linear Discriminant Analyses showed that,
    for the vowel /aː/ alone, spectral tilt showed an advantage over
    intensity, as evidenced by higher stressed/unstressed syllable
    classification accuracy scores for spectral tilt. However, when
    all vowels were included in the analysis, the advantage
    disappeared.
    These findings confirm that spectral tilt plays a larger role
    in signaling stress in Dutch /aː/ but show that, for a larger
    sample of Dutch vowels, overall intensity and spectral tilt are
    equally important.
  • Shi, R., Werker, J., & Cutler, A. (2003). Function words in early speech perception. In Proceedings of the 15th International Congress of Phonetic Sciences (pp. 3009-3012).

    Abstract

    Three experiments examined whether infants recognise functors in phrases, and whether their representations of functors are phonetically well specified. Eight- and 13- month-old English infants heard monosyllabic lexical words preceded by real functors (e.g., the, his) versus nonsense functors (e.g., kuh); the latter were minimally modified segmentally (but not prosodically) from real functors. Lexical words were constant across conditions; thus recognition of functors would appear as longer listening time to sequences with real functors. Eightmonth- olds' listening times to sequences with real versus nonsense functors did not significantly differ, suggesting that they did not recognise real functors, or functor representations lacked phonetic specification. However, 13-month-olds listened significantly longer to sequences with real functors. Thus, somewhere between 8 and 13 months of age infants learn familiar functors and represent them with segmental detail. We propose that accumulated frequency of functors in input in general passes a critical threshold during this time.
  • Slonimska, A., Özyürek, A., & Capirci, O. (2022). Simultaneity as an emergent property of sign languages. In A. Ravignani, R. Asano, D. Valente, F. Ferretti, S. Hartmann, M. Hayashi, Y. Jadoul, M. Martins, Y. Oseki, E. D. Rodrigues, O. Vasileva, & S. Wacewicz (Eds.), The evolution of language: Proceedings of the Joint Conference on Language Evolution (JCoLE) (pp. 678-680). Nijmegen: Joint Conference on Language Evolution (JCoLE).
  • Speed, L., & Majid, A. (2018). Music and odor in harmony: A case of music-odor synaesthesia. In C. Kalish, M. Rau, J. Zhu, & T. T. Rogers (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (CogSci 2018) (pp. 2527-2532). Austin, TX: Cognitive Science Society.

    Abstract

    We report an individual with music-odor synaesthesia who experiences automatic and vivid odor sensations when she hears music. S’s odor associations were recorded on two days, and compared with those of two control participants. Overall, S produced longer descriptions, and her associations were of multiple odors at once, in comparison to controls who typically reported a single odor. Although odor associations were qualitatively different between S and controls, ratings of the consistency of their descriptions did not differ. This demonstrates that crossmodal associations between music and odor exist in non-synaesthetes too. We also found that S is better at discriminating between odors than control participants, and is more likely to experience emotion, memories and evaluations triggered by odors, demonstrating the broader impact of her synaesthesia.

    Additional information

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  • Ten Bosch, L., Ernestus, M., & Boves, L. (2018). Analyzing reaction time sequences from human participants in auditory experiments. In Proceedings of Interspeech 2018 (pp. 971-975). doi:10.21437/Interspeech.2018-1728.

    Abstract

    Sequences of reaction times (RT) produced by participants in an experiment are not only influenced by the stimuli, but by many other factors as well, including fatigue, attention, experience, IQ, handedness, etc. These confounding factors result in longterm effects (such as a participant’s overall reaction capability) and in short- and medium-time fluctuations in RTs (often referred to as ‘local speed effects’). Because stimuli are usually presented in a random sequence different for each participant, local speed effects affect the underlying ‘true’ RTs of specific trials in different ways across participants. To be able to focus statistical analysis on the effects of the cognitive process under study, it is necessary to reduce the effect of confounding factors as much as possible. In this paper we propose and compare techniques and criteria for doing so, with focus on reducing (‘filtering’) the local speed effects. We show that filtering matters substantially for the significance analyses of predictors in linear mixed effect regression models. The performance of filtering is assessed by the average between-participant correlation between filtered RT sequences and by Akaike’s Information Criterion, an important measure of the goodness-of-fit of linear mixed effect regression models.
  • Ten Bosch, L., & Boves, L. (2018). Information encoding by deep neural networks: what can we learn? In Proceedings of Interspeech 2018 (pp. 1457-1461). doi:10.21437/Interspeech.2018-1896.

    Abstract

    The recent advent of deep learning techniques in speech tech-nology and in particular in automatic speech recognition hasyielded substantial performance improvements. This suggeststhat deep neural networks (DNNs) are able to capture structurein speech data that older methods for acoustic modeling, suchas Gaussian Mixture Models and shallow neural networks failto uncover. In image recognition it is possible to link repre-sentations on the first couple of layers in DNNs to structuralproperties of images, and to representations on early layers inthe visual cortex. This raises the question whether it is possi-ble to accomplish a similar feat with representations on DNNlayers when processing speech input. In this paper we presentthree different experiments in which we attempt to untanglehow DNNs encode speech signals, and to relate these repre-sentations to phonetic knowledge, with the aim to advance con-ventional phonetic concepts and to choose the topology of aDNNs more efficiently. Two experiments investigate represen-tations formed by auto-encoders. A third experiment investi-gates representations on convolutional layers that treat speechspectrograms as if they were images. The results lay the basisfor future experiments with recursive networks.
  • Thompson, B., & Lupyan, G. (2018). Automatic estimation of lexical concreteness in 77 languages. In C. Kalish, M. Rau, J. Zhu, & T. T. Rogers (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (CogSci 2018) (pp. 1122-1127). Austin, TX: Cognitive Science Society.

    Abstract

    We estimate lexical Concreteness for millions of words across 77 languages. Using a simple regression framework, we combine vector-based models of lexical semantics with experimental norms of Concreteness in English and Dutch. By applying techniques to align vector-based semantics across distinct languages, we compute and release Concreteness estimates at scale in numerous languages for which experimental norms are not currently available. This paper lays out the technique and its efficacy. Although this is a difficult dataset to evaluate immediately, Concreteness estimates computed from English correlate with Dutch experimental norms at $\rho$ = .75 in the vocabulary at large, increasing to $\rho$ = .8 among Nouns. Our predictions also recapitulate attested relationships with word frequency. The approach we describe can be readily applied to numerous lexical measures beyond Concreteness
  • Thompson, B., Roberts, S., & Lupyan, G. (2018). Quantifying semantic similarity across languages. In C. Kalish, M. Rau, J. Zhu, & T. T. Rogers (Eds.), Proceedings of the 40th Annual Conference of the Cognitive Science Society (CogSci 2018) (pp. 2551-2556). Austin, TX: Cognitive Science Society.

    Abstract

    Do all languages convey semantic knowledge in the same way? If language simply mirrors the structure of the world, the answer should be a qualified “yes”. If, however, languages impose structure as much as reflecting it, then even ostensibly the “same” word in different languages may mean quite different things. We provide a first pass at a large-scale quantification of cross-linguistic semantic alignment of approximately 1000 meanings in 55 languages. We find that the translation equivalents in some domains (e.g., Time, Quantity, and Kinship) exhibit high alignment across languages while the structure of other domains (e.g., Politics, Food, Emotions, and Animals) exhibits substantial cross-linguistic variability. Our measure of semantic alignment correlates with known phylogenetic distances between languages: more phylogenetically distant languages have less semantic alignment. We also find semantic alignment to correlate with cultural distances between societies speaking the languages, suggesting a rich co-adaptation of language and culture even in domains of experience that appear most constrained by the natural world

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