Publications

Abstract

Grice in pragmatics and Levelt in psycholinguistics have proposed models of human communication where the starting point of communicative action is an individual intention. This assumption, though, has to face serious objections with regard to the alleged existence of explicit representations of the communicative goals to be pursued. Here evidence is surveyed which shows that in fact speaking may ordinarily be a quite automatic activity prompted by contextual cues and driven by behavioural schemata abstracted away from social regularities. On the one hand, this means that there could exist no intentions in the sense of explicit representations of communicative goals, following from deliberate reasoning and triggering the communicative action. On the other hand, however, there are reasons to allow for a weaker notion of intention than this, according to which communication is an intentional affair, after all. Communicative action is said to be intentional in this weaker sense to the extent that it is subject to a double mechanism of control, with respect both to present-directed and future-directed intentions.

Abstract

The goal of the presented study was to investigate the use of coarticulatory vowel nasalization in lexical access by native speakers of American English. In particular, we compare the use of coart culatory place of articulation cues to that of coarticulatory vowel nasalization. Previous research on lexical access has shown that listeners use cues to the place of articulation of a postvocalic stop in the preceding vowel. However, vowel nasalization as cue to an upcoming nasal consonant has been argued to be a more complex phenomenon. In order to establish whether coarticulatory vowel nasalization aides in the process of lexical access in the same way as place of articulation cues do, we conducted two perception experiments: an off-line 2AFC discrimination task and an on-line eyetracking study using the visual world paradigm. The results of our study suggest that listeners are indeed able to use vowel nasalization in similar ways to place of articulation information, and that both types of cues aide in lexical access.

Abstract

The results of a word-spotting experiment are presented in which Dutch listeners tried to spot different types of bisyllabic Dutch words embedded in different types of nonsense contexts. Embedded verbs were not reliably harder to spot than embedded nouns; this suggests that nouns and verbs are recognised via the same basic processes. Iambic words were no harder to spot than trochaic words, suggesting that trochaic words are not in principle easier to recognise than iambic words. Words were harder to spot in consonantal contexts (i.e., contexts which themselves could not be words) than in longer contexts which contained at least one vowel (i.e., contexts which, though not words, were possible words of Dutch). A control experiment showed that this difference was not due to acoustic differences between the words in each context. The results support the claim that spoken-word recognition is sensitive to the viability of sound sequences as possible words.

Abstract

This paper presents an analysis of semantic association norms for German nouns. In contrast to prior studies, we not only collected associations elicited by written representations of target objects but also by their pictorial representations. In a first analysis, we identified systematic differences in the type and distribution of associate responses for the two presentation forms. In a second analysis, we applied a soft cluster analysis to the collected target-response pairs. We subsequently used the clustering to predict noun ambiguity and to discriminate senses in our target nouns.

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.

Abstract

Listeners use lexical knowledge to judge what speech sounds they heard. I investigated whether such lexical influences are truly top-down or just reflect a merging of perceptual and lexical constraints. This is achieved by testing whether the lexically determined identity of a phone exerts the appropriate context effects on surrounding phones. The current investigations focuses on compensation for coarticulation in vowel-fricative sequences, where the presence of a rounded vowel (/y/ rather than /i/) leads fricatives to be perceived as /s/ rather than //. This results was consistently found in all three experiments. A vowel was also more likely to be perceived as rounded /y/ if that lead listeners to be perceive words rather than nonwords (Dutch: meny, English id. vs. meni nonword). This lexical influence on the perception of the vowel had, however, no consistent influence on the perception of following fricative.

Abstract

We investigated perception of words with reduced word-final /t/ using an adapted eyetracking paradigm. Dutch listeners followed spoken instructions to click on printed words which were accompanied on a computer screen by simple shapes (e.g., a circle). Targets were either above or next to their shapes, and the shapes uniquely identified the targets when the spoken forms were ambiguous between words with or without final /t/ (e.g., bult, bump, vs. bul, diploma). Analysis of listeners’ eye-movements revealed, in contrast to earlier results, that listeners use the following segmental context when compensating for /t/-reduction. Reflecting that /t/-reduction is more likely to occur before bilabials, listeners were more likely to look at the /t/-final words if the next word’s first segment was bilabial. This result supports models of speech perception in which prelexical phonological processes use segmental context to modulate word recognition.

Abstract

To assess the reality of phonological features in language processing (vs. language description), one needs to specify the distinctive claims of distinctive-feature theory. Two of the more farreaching claims are compositionality and generalizability. I will argue that there is some evidence for the first and evidence against the second claim from a recent behavioral paradigm. Highlighting the contribution of a behavioral paradigm also counterpoints the use of brain measures as the only way to elucidate what is "real for the brain". The contributions of the speakers exemplify how brain measures can help us to understand the reality of phonological features in language processing. The evidence is, however, not convincing for a) the claim for underspecification of phonological features—which has to deal with counterevidence from behavioral as well as brain measures—, and b) the claim of position independence of phonological features.

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.

Abstract

Corpus linguistics and language documentation are usually considered separate subdisciplines within linguistics, having developed from different traditions and often operating on different scales, but the authors will suggest that there are commonalities to the two: both aim to represent language use in a community, and both are concerned with managing digital data. The authors propose that the development of the Australian National Corpus (AusNC) be guided by the experience of language documentation in the management of multimodal digital data and its annotation, and in ethical issues pertaining to making the data accessible. This would allow an AusNC that is distributed, multimodal, and multilingual, with holdings of text, audio, and video data distributed across multiple institutions; and including Indigenous, sign, and migrant community languages. An audit of language material held by Australian institutions and individuals is necessary to gauge the diversity and volume of possible content, and to inform common technical standards.

Abstract

Studies have shown that listeners segmenting unfamiliar languages transfer native-language (L1) segmentation cues. These studies, however, conflated L1 and recent linguistic exposure. The present study investigates the relative influences of L1 and recent linguistic exposure on the use of prosodic cues for segmenting an artificial language (AL). Participants were L1-French listeners, high-proficiency L2-French L1-English listeners, and L1-English listeners without functional knowledge of French. The prosodic cue assessed was F0 rise, which is word-final in French, but in English tends to be word-initial. 30 participants heard a 20-minute AL speech stream with word-final boundaries marked by F0 rise, and decided in a subsequent listening task which of two words (without word-final F0 rise) had been heard in the speech stream. The analyses revealed a marginally significant effect of L1 (all listeners) and, importantly, a significant effect of recent linguistic exposure (L1-French and L2-French listeners): accuracy increased with decreasing time in the US since the listeners’ last significant (3+ months) stay in a French-speaking environment. Interestingly, no effect of L2 proficiency was found (L2-French listeners).

Abstract

Language resources can be divided into structural resources treating phonology, morphosyntax, semantics etc. and resources treating the social, demographic, ethnic, political context. A third type are meta-resources, like bibliographies, which provide access to the resources of the first two kinds. This poster will present the Glottolog/Langdoc project, a comprehensive bibliography providing web access to 180k bibliographical records to (mainly) low visibility resources from low-density languages. The resources are annotated for macro-area, content language, and document type and are available in XHTML and RDF.

Abstract

Frontotemporal lobar degeneration (FTLD) is a group of neurodegenerative conditions characterised by focal frontal and/or temporal lobe atrophy. Patients develop a range of cognitive and behavioural abnormalities, including prominent difficulties in comprehending and expressing emotions, with significant clinical and social consequences. Here we report a systematic prospective analysis of emotion processing in different input modalities in patients with FTLD. We examined recognition of happiness, sadness, fear and anger in facial expressions, non-verbal vocalisations and music in patients with FTLD and in healthy age matched controls. The FTLD group was significantly impaired in all modalities compared with controls, and this effect was most marked for music. Analysing each emotion separately, recognition of negative emotions was impaired in all three modalities in FTLD, and this effect was most marked for fear and anger. Recognition of happiness was deficient only with music. Our findings support the idea that FTLD causes impaired recognition of emotions across input channels, consistent with a common central representation of emotion concepts. Music may be a sensitive probe of emotional deficits in FTLD, perhaps because it requires a more abstract representation of emotion than do animate stimuli such as faces and voices.

Abstract

Japanese listeners detected Japanese words embedded at the end of nonsense sequences (e.g., kaba 'hippopotamus' in gyachikaba). When the final portion of the preceding context together with the initial portion of the word (e.g., here, the sequence chika) was compatible with many lexical competitors, recognition of the embedded word was more difficult than when such a sequence was compatible with few competitors. This clear effect of competition, established here for preceding context in Japanese, joins similar demonstrations, in other languages and for following contexts, to underline that the functional architecture of the human spoken-word recognition system is a universal one.

Abstract

In this paper we try to contribute to the body of knowledge about the acquisition of English epistemic modal verbs (e.g. Mary may/has to be at school). Semantically, these verbs encode possibility or necessity with respect to available evidence. Pragmatically, the use of epistemic modals often gives rise to scalar conversational inferences (Mary may be at school -> Mary doesn’t have to be at school). The acquisition of epistemic modals is challenging for children on both these levels. In this paper, we present findings from two studies which were conducted with 5-year-old children and adults. Our findings, unlike previous work, show that 5-yr-olds have mastered epistemic modal semantics, including the notions of necessity and possibility. However, they are still in the process of acquiring epistemic modal pragmatics.

Abstract

En este artículo se desarrolla un método automático de segmentación de fonemas no supervisado. Este método utiliza el algoritmo de agrupación de máximo margen [1] para realizar segmentación de fonemas sobre habla continua sin necesidad de información a priori para el entrenamiento del sistema.

Abstract

This study investigates whether the acoustic durations of derivational affixes in Dutch are affected by the frequency of the word they occur in. In a word naming experiment, subjects were presented with a large number of words containing one of the affixes ge-, ver-, ont, or -lijk. Their responses were recorded on DAT tapes, and the durations of the affixes were measured using Automatic Speech Recognition technology. To investigate whether frequency also affected durations when speech rate was high, the presentation rate of the stimuli was varied. The results show that a higher frequency of the word as a whole led to shorter acoustic realizations for all affixes. Furthermore, affixes became shorter as the presentation rate of the stimuli increased. There was no interaction between word frequency and presentation rate, suggesting that the frequency effect also applies in situations in which the speed of articulation is very high.

Abstract

Two eye-tracking experiments tested whether native listeners can adapt
to reductions in casual Dutch speech. Listeners were exposed to segmental
([b] > [m]), syllabic (full-vowel-deletion), or no reductions. In a subsequent
test phase, all three listener groups were tested on how efficiently they could
recognize both types of reduced words. In the first Experiment’s exposure
phase, the (un)reduced target words were predictable. The segmental reductions
were completely consistent (i.e., involved the same input sequences).
Learning about them was found to be pattern-specific and generalized in the
test phase to new reduced /b/-words. The syllabic reductions were not consistent
(i.e., involved variable input sequences). Learning about them was
weak and not pattern-specific. Experiment 2 examined effects of word repetition
and predictability. The (un-)reduced test words appeared in the exposure
phase and were not predictable. There was no evidence of learning for
the segmental reductions, probably because they were not predictable during
exposure. But there was word-specific learning for the vowel-deleted words.
The results suggest that learning about reductions is pattern-specific and
generalizes to new words if the input is consistent and predictable. With
variable input, there is more likely to be adaptation to a general speaking
style and word-specific learning.

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.

Abstract

Cognitive research is often focused on experimental condition-driven reactions. Ethological studies frequently
rely on the observation of naturally occurring specific behaviors. In both cases, subjects are filmed during the
study, so that afterwards behaviors can be coded on video. Coding should typically be blind to experimental
conditions, but often requires more information than that present on video. We introduce a method for blindcoding
of behavioral videos that takes care of both issues via three main innovations. First, of particular
significance for playback studies, it allows creation of a “soundtrack” of the study, that is, a track composed of
synthesized sounds representing different aspects of the experimental conditions, or other events, over time.
Second, it facilitates coding behavior using this audio track, together with the possibly muted original video.
This enables coding blindly to conditions as required, but not ignoring other relevant events. Third, our method
makes use of freely available, multi-platform software, including scripts we developed.

Abstract

To understand spoken words listeners have to cope with seemingly meaningless variability in the speech signal. Speakers vary, for example, their tone of voice (ToV) by changing speaking rate, pitch, vocal effort, and loudness. This variation is independent of "linguistic prosody" such as sentence intonation or speech rhythm. The variation due to ToV, however, is not random. Speakers use, for example, higher pitch when referring to small objects than when referring to large objects and importantly, adult listeners are able to use these non-lexical ToV cues to distinguish between the meanings of antonym pairs (e.g., big-small; Nygaard, Herold, & Namy, 2009). In the present study, we asked whether listeners infer the meaning of novel adjectives from ToV and subsequently interpret these adjectives according to the learned meaning even in the absence of ToV. Moreover, if listeners actually acquire these adjectival meanings, then they should generalize these word meanings to novel referents. ToV would thus be a semantic cue to lexical acquisition. This hypothesis was tested in an exposure-test paradigm with adult listeners. In the experiment listeners' eye movements to picture pairs were monitored. The picture pairs represented the endpoints of the adjectival dimensions big-small, hot-cold, and strong-weak (e.g., an elephant and an ant represented big-small). Four picture pairs per category were used. While viewing the pictures participants listened to lexically unconstraining sentences containing novel adjectives, for example, "Can you find the foppick one?" During exposure, the sentences were spoken in infant-directed speech with the intended adjectival meaning expressed by ToV. Word-meaning pairings were counterbalanced across participants. Each word was repeated eight times. Listeners had no explicit task. To guide listeners' attention to the relation between the words and pictures, three sets of filler trials were included that contained real English adjectives (e.g., full-empty). In the subsequent test phase participants heard the novel adjectives in neutral adult-directed ToV. Test sentences were recorded before the speaker was informed about intended word meanings. Participants had to choose which of two pictures on the screen the speaker referred to. Picture pairs that were presented during the exposure phase and four new picture pairs per category that varied along the critical dimensions were tested. During exposure listeners did not spontaneously direct their gaze to the intended referent at the first presentation. But as indicated by listener's fixation behavior, they quickly learned the relationship between ToV and word meaning over only two exposures. Importantly, during test participants consistently identified the intended referent object even in the absence of informative ToV. Learning was found for all three tested categories and did not depend on whether the picture pairs had been presented during exposure. Listeners thus use ToV not only to distinguish between antonym pairs but they are able to extract word meaning from ToV and assign this meaning to novel words. The newly learned word meanings can then be generalized to novel referents even in the absence of ToV cues. These findings suggest that ToV can be used as a semantic cue to lexical acquisition. References Nygaard, L. C., Herold, D. S., & Namy, L. L. (2009) The semantics of prosody: Acoustic and perceptual evidence of prosodic correlates to word meaning. Cognitive Science, 33. 127-146.

Abstract

A aquisição da leitura decorre ao longo de diversas etapas, desde o momento em que a criança inicia o contacto com o alfabeto até ao momento em que se torna um leitor competente, apto a ler correcta e fluentemente. Compreender a evolução desta competência através de uma análise da diferenciação do peso de variáveis preditoras da leitura possibilita teorizar sobre os mecanismos cognitivos envolvidos nas diferentes fases de desenvolvimento da leitura. Realizámos um estudo transversal com 568 alunos do segundo ao quarto ano do primeiro ciclo do Ensino Básico, em que se avaliou o impacto de capacidades de processamento fonológico, nomeação rápida, conhecimento letra-som e vocabulário, bem como de capacidades cognitivas mais gerais (inteligência não-verbal e memória de trabalho), na exactidão e velocidade da leitura. De uma forma geral, os resultados mostraram que, apesar da consciência fonológica permanecer como o preditor mais importante da exactidão e fluência da leitura, o seu peso decresce à medida que a escolaridade aumenta. Observou-se também que, à medida que o contributo da consciência fonológica para a explicação da velocidade de leitura diminuía, aumentava o contributo de outras variáveis mais associadas ao automatismo e reconhecimento lexical, tais como a nomeação rápida e o vocabulário. Em suma, podemos dizer que ao longo da escolaridade se observa uma alteração dinâmica dos processos cognitivos subjacentes à leitura, o que sugere que a criança evolui de uma estratégia de leitura ancorada em processamentos sub-lexicais, e como tal mais dependente de processamentos fonológicos, para uma estratégia baseada no reconhecimento ortográfico das palavras.

Abstract

This paper reports on the development of a flexible web based lexicon tool, LEXUS. LEXUS is targeted at linguists involved in language documentation (of endangered languages). It allows the creation of lexica within the structure of the proposed ISO LMF standard and uses the proposed concept naming conventions from the ISO data categories, thus enabling interoperability, search and merging. LEXUS also offers the possibility to visualize language, since it provides functionalities to include audio, video and still images to the lexicon. With LEXUS it is possible to create semantic network knowledge bases, using typed relations. The LEXUS tool is free for use. Index Terms: lexicon, web based application, endangered languages, language documentation.

Abstract

LEXUS and ViCoS: from lexicon to conceptual spaces LEXUS is a web-based lexicon tool and the knowledge space software ViCoS is an extension of LEXUS, allowing users to create relations between objects in and across lexica. LEXUS and ViCoS are part of the Language Archiving Technology software, developed at the MPI for Psycholinguistics to archive and enrich linguistic resources collected in the framework of language documentation projects. LEXUS is of primary interest for language documentation, offering the possibility to not just create a digital dictionary, but additionally it allows the creation of multi-media encyclopedic lexica. ViCoS provides an interface between the lexical space and the ontological space. Its approach permits users to model a world of concepts and their interrelations based on categorization patterns made by the speech community. We describe the LEXUS and ViCoS functionalities using three cases from DoBeS language documentation projects: (1) Marquesan The Marquesan lexicon was initially created in Toolbox and imported into LEXUS using the Toolbox import functionality. The lexicon is enriched with multi-media to illustrate the meaning of the words in its cultural environment. Members of the speech community consider words as keys to access and describe relevant parts of their life and traditions. Their understanding of words is best described by the various associations they evoke rather than in terms of any formal theory of meaning. Using ViCoS a knowledge space of related concepts is being created. (2) Kola-Sámi Two lexica are being created in LEXUS: RuSaDic lexicon is a Russian-Kildin wordlist in which the entries are of relative limited structure and content. SaRuDiC is a more complex structured lexicon with much richer content, including multi-media fragments and derivations. Using ViCoS we have created a connection between the two lexica, so that speakers who are familiair with Russian and wish to revitalize their Kildin can enter the lexicon through the RuSaDic and from there approach the informative SaRuDic. Similary we will create relations from the two lexica to external open databases, like e.g. Álgu. (3) Beaver A speaker database including kinship relations has been created and the database has been imported into LEXUS. In the LEXUS views the relations for individual speakers are being displayed. Using ViCoS the relational information from the database will be extracted to form a kisnhip relation space with specific relation types, like e.g 'mother-of'. The whole set of relations from the database can be displayed in one ViCoS relation window, and zoom functionality is available.

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.

Abstract

In this paper, I will give an overview of some well-studied multimodal signals that humans produce while they communicate with other humans, and discuss the implications of those studies for HCI. I will first discuss a conceptual framework that allows us to distinguish between functional and sensory modalities. This distinction is important, as there are multiple functional modalities using the same sensory modality (e.g., facial expression and eye-gaze in the visual modality). A second theoretically important issue is redundancy. Some signals appear to be redundant with a signal in another modality, whereas others give new information or even appear to give conflicting information (see e.g., the work of Susan Goldin-Meadows on speech accompanying gestures). I will argue that multimodal signals are never truly redundant. First, many gestures that appear at first sight to express the same meaning as the accompanying speech generally provide extra (analog) information about manner, path, etc. Second, the simple fact that the same information is expressed in more than one modality is itself a communicative signal. Armed with this conceptual background, I will then proceed to give an overview of some multimodalsignals that have been investigated in human-human research, and the level of understanding we have of the meaning of those signals. The latter issue is especially important for potential implementations of these signals in artificial agents. First, I will discuss pointing gestures. I will address the issue of the timing of pointing gestures relative to the speech it is supposed to support, the mutual dependency between pointing gestures and speech, and discuss the existence of alternative ways of pointing from other cultures. The most frequent form of pointing that does not involve the index finger is a cultural practice called lip-pointing which employs two visual functional modalities, mouth-shape and eye-gaze, simultaneously for pointing. Next, I will address the issue of eye-gaze. A classical study by Kendon (1967) claims that there is a systematic relationship between eye-gaze (at the interlocutor) and turn-taking states. Research at our institute has shown that this relationship is weaker than has often been assumed. If the dialogue setting contains a visible object that is relevant to the dialogue (e.g., a map), the rate of eye-gaze-at-other drops dramatically and its relationship to turn taking disappears completely. The implications for machine generated eye-gaze are discussed. Finally, I will explore a theoretical debate regarding spontaneous gestures. It has often been claimed that the class of gestures that is called iconic by McNeill (1992) are a “window into the mind”. That is, they are claimed to give the researcher (or even the interlocutor) a direct view into the speaker’s thought, without being obscured by the complex transformation that take place when transforming a thought into a verbal utterance. I will argue that this is an illusion. Gestures can be shown to be specifically designed such that the listener can be expected to interpret them. Although the transformations carried out to express a thought in gesture are indeed (partly) different from the corresponding transformations for speech, they are a) complex, and b) severely understudied. This obviously has consequences both for the gesture research agenda, and for the generation of iconic gestures by machines.

Abstract

The current study reports specific cases in which a positive transfer of perceptual ability from the music domain to the language domain occurs. We tested whether musical training enhances discrimination and identification performance of L2 speech sounds (timing features, nasal consonants and vowels). Native Dutch and Japanese speakers with different musical training experience, matched for their estimated verbal IQ, participated in the experiments. Results indicated that musical training strongly increases one’s ability to perceive timing information in speech signals. We also found a benefit of musical training on discrimination performance for a subset of the tested vowel contrasts.

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.

Abstract

Despite differences in language, culture, and ecology, some human characteristics are similar in people all over the world, while other features vary from one group to the next. These similarities and differences can inform arguments about what aspects of the human mind are part of our shared biological heritage and which are predominantly products of culture and language. I will present data from a cross-cultural project investigating the recognition of non-verbal vocalizations of emotions, such as screams and laughs, across two highly different cultural groups. English participants were compared to individuals from remote, culturally isolated Namibian villages. Vocalizations communicating the so-called “basic emotions” (anger, disgust, fear, joy, sadness, and surprise) were bidirectionally recognised. In contrast, a set of additional positive emotions was only recognised within, but not across, cultural boundaries. These results indicate that a number of primarily negative emotions are associated with vocalizations that can be recognised across cultures, while at least some positive emotions are communicated with culture-specific signals. I will discuss these findings in the context of accounts of emotions at differing levels of analysis, with an emphasis on the often-neglected positive emotions.

Abstract

Many studies suggest that emotional signals can be recognized across cultures and modalities. But to what extent are these signals innate and to what extent are they learned? This study investigated whether auditory learning is necessary for the production of recognizable emotional vocalizations by examining the vocalizations produced by people born deaf. Recordings were made of eight congenitally deaf Dutch individuals, who produced non-verbal vocalizations of a range of negative and positive emotions. Perception was examined in a forced-choice task with hearing Dutch listeners (n = 25). Considerable variability was found across emotions, suggesting that auditory learning is more important for the acquisition of certain types of vocalizations than for others. In particular, achievement and surprise sounds were relatively poorly recognized. In contrast, amusement and disgust vocalizations were well recognized, suggesting that for some emotions, recognizable vocalizations can develop without any auditory learning. The implications of these results for models of emotional communication are discussed, and other routes of social learning available to the deaf individuals are considered.

Abstract

Vocalizations like screams and laughs are used to communicate affective states, but what acoustic cues in these signals require vocal learning and which ones are innate? This study investigated the role of auditory learning in the production of non-verbal emotional vocalizations by examining the vocalizations produced by people born deaf. Recordings were made of congenitally deaf Dutch individuals and matched hearing controls, who produced non-verbal vocalizations of a range of negative and positive emotions. Perception was examined in a forced-choice task with hearing Dutch listeners (n = 25), and judgments were analyzed together with acoustic cues, including envelope, pitch, and spectral measures. Considerable variability was found across emotions and acoustic cues, and the two types of information were related for a sub-set of the emotion categories. These results suggest that auditory learning is less important for the acquisition of certain types of vocalizations than for others (particularly amusement and relief), and they also point to a less central role for auditory learning of some acoustic features in affective non-verbal vocalizations. The implications of these results for models of vocal emotional communication are discussed.

Abstract

Emotional signals allow for the sharing of important information with conspecifics, for example to warn them of danger. Humans use a range of different cues to communicate to others how they feel, including facial, vocal, and gestural signals. Although much is known about facial expressions of emotion, less research has focused on affect in the voice. We compare British listeners to individuals from remote Namibian villages who have had no exposure to Western culture, and examine recognition of non-verbal emotional vocalizations, such as screams and laughs. We show that a number of emotions can be universally recognized from non-verbal vocal signals. In addition we demonstrate the specificity of this pattern, with a set of additional emotions only recognized within, but not across these cultural groups. Our findings indicate that a small set of primarily negative emotions have evolved signals across several modalities, while most positive emotions are communicated with culture-specific signals.

Abstract

The difficulty of the task of segmenting a speech signal into its words is immediately clear when listening to a foreign language; it is much harder to segment the signal into its words, since the words of the language are unknown. Infants are faced with the same task when learning their first language. This study provides a better understanding of the task that infants face while learning their native language. We employed an automatic algorithm on the task of speech segmentation without prior knowledge of the labels of the phonemes. An analysis of the boundaries erroneously placed inside a phoneme showed that the algorithm consistently placed additional boundaries in phonemes in which acoustic changes occur. These acoustic changes may be as great as the transition from the closure to the burst of a plosive or as subtle as the formant transitions in low or back vowels. Moreover, we found that glottal vibration may attenuate the relevance of acoustic changes within obstruents. An interesting question for further research is how infants learn to overcome the natural tendency to segment these ‘dynamic’ phonemes.

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.

Abstract

Articulatory feature (AF) modelling of speech has received a considerable amount of attention in automatic speech recognition research. Although termed ‘articulatory’, previous definitions make certain assumptions that are invalid, for instance, that articulators ‘hop’ from one fixed position to the next. In this paper, we studied two methods, based on support vector classification (SVC) and regression (SVR), in which the articulation continuum is modelled without being restricted to using discrete AF value classes. A comparison with a baseline system trained on quantised values of the articulation continuum showed that both SVC and SVR outperform the baseline for two of the three investigated AFs, with improvements up to 5.6% absolute.

Abstract

The ultimate goal of our research is to develop a computational model of human speech recognition that is able to capture the effects of fine-grained acoustic variation on speech recognition behaviour. As part of this work we are investigating automatic feature classifiers that are able to create reliable and accurate transcriptions of the articulatory behaviour encoded in the acoustic speech signal. In the experiments reported here, we compared support vector machines (SVMs) with multilayer perceptrons (MLPs). MLPs have been widely (and rather successfully) used for the task of multi-value articulatory feature classification, while (to the best of our knowledge) SVMs have not. This paper compares the performances of the two classifiers and analyses the results in order to better understand the articulatory representations. It was found that the MLPs outperformed the SVMs, but it is concluded that both classifiers exhibit similar behaviour in terms of patterns of errors.

Abstract

In foreign-accented speech, pronunciation typically deviates from the canonical form to some degree. For native listeners, it has been shown that word recognition is more difficult for strongly-accented words than for less strongly-accented words. Furthermore recognition of strongly-accented words becomes easier with additional exposure to the foreign accent. In this paper, listeners’ behaviour was simulated with Fine-tracker, a computational model of word recognition that uses real speech as input. The simulations showed that, in line with human listeners, 1) Fine-Tracker’s recognition outcome is modulated by the degree of accentedness and 2) it improves slightly after brief exposure with the accent. On the level of individual words, however, Fine-tracker failed to correctly simulate listeners’ behaviour, possibly due to differences in overall familiarity with the chosen accent (German-accented Dutch) between human listeners and Fine-Tracker.

Abstract

Aging often affects sensitivity to the higher frequencies, which results in the loss of sensitivity to phonetic detail in speech. Hearing loss may therefore interfere with the categorisation of two consonants that have most information to differentiate between them in those higher frequencies and less in the lower frequencies, e.g., /f/ and /s/. We investigate two acoustic cues, i.e., formant transitions and fricative intensity, that older listeners might use to differentiate between /f/ and /s/. The results of two phonetic categorisation tasks on 38 older listeners (aged 60+) with varying degrees of hearing loss indicate that older listeners seem to use formant transitions as a cue to distinguish /s/ from /f/. Moreover, this ability is not impacted by hearing loss. On the other hand, listeners with increased hearing loss seem to rely more on intensity for fricative identification. Thus, progressive hearing loss may lead to gradual changes in perceptual cue weighting.

Abstract

A stretch of speech is often consistent with multiple words, e.g., the sequence /hæm/ is consistent with ‘ham’ but also with the first syllable of ‘hamster’, resulting in temporary ambiguity. However, to what degree does this lexical embedding occur? Analyses on two corpora of spoken Dutch showed that 11.9%-19.5% of polysyllabic word tokens have word-initial embedding, while 4.1%-7.5% of monosyllabic word tokens can appear word-initially embedded. This is much lower than suggested by an analysis of a large dictionary of Dutch. Speech processing thus appears to be simpler than one might expect on the basis of statistics on a dictionary.

Abstract

Young listeners can quickly modify their interpretation of a speech sound when a talker produces the sound ambiguously. Young Dutch listeners rely mainly on the higher frequencies to distinguish between /f/ and /s/, but these higher frequencies are particularly vulnerable to age-related hearing loss. We therefore tested whether older Dutch listeners can show perceptual retuning given an ambiguous pronunciation in between /f/ and /s/. Results of a lexically-guided perceptual learning experiment showed that older Dutch listeners are still able to learn non-standard pronunciations of /f/ and /s/. Possibly, the older listeners have learned to rely on other acoustic cues, such as formant transitions, to distinguish between /f/ and /s/. However, the size and duration of the perceptual effect is influenced by hearing loss, with listeners with poorer hearing showing a smaller and a shorter-lived learning effect.

Abstract

Evidence that listeners use durational cues to help resolve temporarily ambiguous speech input has accumulated over the past few years. In this paper, we investigate whether durational cues are also beneficial for word recognition in a computational model of spoken-word recognition. Two sets of simulations were carried out using the acoustic signal as input. The simulations showed that the computational model, like humans, takes benefit from durational cues during word recognition, and uses these to disambiguate the speech signal. These results thus provide support for the theory that durational cues play a role in spoken-word recognition.

Abstract

Good teachers know their students, and exploit this knowledge to adapt or optimise their instruction. Traditional teachers know their students because they interact with them face-to-face in classroom or one-to-one tutoring sessions. In these settings, they can build student models, i.e., by exploiting the multi-faceted nature of human-human communication. In distance-learning contexts, teacher and student have to cope with the lack of such direct interaction, and this must have detrimental effects for both teacher and student. In a past study we have analysed teacher requirements for tracking student actions in computer-mediated settings. Given the results of this study, we have devised and implemented a tool that allows teachers to keep track of their learners'interaction in e-learning systems. We present the tool's functionality and user interfaces, and an evaluation of its usability.

Abstract

This paper presents a study on the acoustic sub-segmental properties of word-final /t/ in conversational standard Dutch and how these properties contribute to whether humans and an ASR system classify the /t/ as acoustically present or absent. In general, humans and the ASR system use the same cues (presence of a constriction, a burst, and alveolar frication), but the ASR system is also less sensitive to fine cues (weak bursts, smoothly starting friction) than human listeners and misled by the presence of glottal vibration. These data inform the further development of models of human and automatic speech processing.

Abstract

This paper presents a study on the reduction of word-final [t]s in conversational standard Dutch. Based on a large amount of tokens annotated on the segmental level, we show that the bigram frequency and the segmental context are the main predictors for the absence of [t]s. In a second study, we present an analysis of the detailed acoustic properties of word-final [t]s and we show that bigram frequency and context also play a role on the subsegmental level. This paper extends research on the realization of /t/ in spontaneous speech and shows the importance of incorporating sub-segmental properties in models of speech.

Abstract

This presentation will address aspects of the expression of emotion in non-verbal vocal behaviour, specifically attempting to determine the roles of both positive and negative emotions, their acoustic bases, and the extent to which these are recognized in non-Western cultures.

Abstract

One of the many results of the "Space" research project conducted at the MPI for Psycholinguistics is that there are three "Frames of spatial Reference" (FoRs), the relative, the intrinsic and the absolute FoR. Cross-linguistic research showed that speakers who prefer one FoR in verbal spatial references rely on a comparable coding system for memorizing spatial configurations and for making inferences with respect to these spatial configurations in non-verbal problem solving. Moreover, research results also revealed that in some languages these verbal FoRs also influence gestural behavior. These results document the close interrelationship between language, culture and cognition in the domain "Space". The proper description of these interrelationships in the spatial domain requires language and culture specific ontologies.

Abstract

The present paper is part of a large research programme investigating the nature and properties of the predicate logic inherent in natural language. The general hypothesis is that natural speakers start off with a basic-natural logic, based on natural cognitive functions, including the basic-natural way of dealing with plural objects. As culture spreads, functional pressure leads to greater generalization and mathematical correctness, yielding ever more refined systems until the apogee of standard modern predicate logic. Four systems of predicate calculus are considered: Basic-Natural Predicate Calculus (BNPC), Aritsotelian-Abelardian Predicate Calculus (AAPC), Aritsotelian-Boethian Predicate Calculus (ABPC), also known as the classic Square of Opposition, and Standard Modern Predicate Calculus (SMPC). (ABPC is logically faulty owing to its Undue Existential Import (UEI), but that fault is repaired by the addition of a presuppositional component to the logic.) All four systems are checked against seven natural logical intuitions. It appears that BNPC scores best (five out of seven), followed by ABPC (three out of seven). AAPC and SMPC finish ex aequo with two out of seven.

Abstract

Spontal-N is a corpus of spontaneous, interactional Norwegian. To our knowledge, it is the first corpus of Norwegian in which the majority of speakers have spent significant parts of their lives in Sweden, and in which the recorded speech displays varying degrees of interference from Swedish. The corpus consists of studio quality audio- and video-recordings of four 30-minute free conversations between acquaintances, and a manual orthographic transcription of the entire material. On basis of the orthographic transcriptions, we automatically annotated approximately 50 percent of the material on the phoneme level, by means of a forced alignment between the acoustic signal and pronunciations listed in a dictionary. Approximately seven percent of the automatic transcription was manually corrected. Taking the manual correction as a gold standard, we evaluated several sources of pronunciation variants for the automatic transcription. Spontal-N is intended as a general purpose speech resource that is also suitable for investigating phonetic detail.

Abstract

When perceiving vowels, listeners adjust to speaker-specific vocal-tract characteristics (such as F1) through "extrinsic vowel normalization". This effect is observed as a shift in the location of categorization boundaries of vowel continua. Similar effects have been found with non-speech. Non-speech materials, however, have consistently led to smaller effect-sizes, perhaps because of a lack of attention to non-speech. The present study investigated this possibility. Non-speech materials that had previously been shown to elicit reduced normalization effects were tested again, with the addition of an attention manipulation. The results show that increased attention does not lead to increased normalization effects, suggesting that vowel normalization is mainly determined by bottom-up signal characteristics.

Abstract

ELAN is a versatile multimedia annotation tool that is being developed at the Max Planck Institute for Psycholinguistics. About a decade ago it emerged out of a number of corpus tools and utilities and it has been extended ever since. This paper focuses on the efforts made to ensure that the application keeps up with the growing needs of that era in linguistics and multimodality research; growing needs in terms of length and resolution of recordings, the number of recordings made and transcribed and the number of levels of annotation per transcription.

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.

Abstract

This paper presents the Kachna corpus of spontaneous speech, in which ten Czech and ten Norwegian speakers were recorded both in their native language and in English. The dialogues are elicited using a picture replication task that requires active cooperation and interaction of speakers by asking them to produce a drawing as close to the original as possible. The corpus is appropriate for the study of interactional features and speech reduction phenomena across native and second languages. The combination of productions in non-native English and in speakers’ native language is advantageous for investigation of L2 issues while providing a L1 behaviour reference from all the speakers. The corpus consists of 20 dialogues comprising 12 hours 53 minutes of recording, and was collected in 2008. Preparation of the transcriptions, including a manual orthographic transcription and an automatically generated phonetic transcription, is currently in progress. The phonetic transcriptions are automatically generated by aligning acoustic models with the speech signal on the basis of the orthographic transcriptions and a dictionary of pronunciation variants compiled for the relevant language. Upon completion the corpus will be made available via the European Language Resources Association (ELRA).

Abstract

Why do people accommodate to each other’s linguistic behavior? Studies of natural interactions (Giles, Taylor & Bourhis, 1973) suggest that speakers accommodate to achieve interactional goals, influencing what their interlocutor thinks or feels about them. But is this the only reason speakers accommodate? In real-world conversations, interactional motivations are ubiquitous, making it difficult to assess the extent to which they drive accommodation. Do speakers still accommodate even when interactional goals cannot be achieved, for instance, when their interlocutor cannot interpret their accommodation behavior? To find out, we asked participants to enter an immersive virtual reality (VR) environment and to converse with a virtual interlocutor. Participants accommodated to the speech rate of their virtual interlocutor even though he could not interpret their linguistic behavior, and thus accommodation could not possibly help them to achieve interactional goals. Results show that accommodation does not require explicit interactional goals, and suggest other social motivations for accommodation.

Abstract

In this article, we propose the use of suffix arrays to efficiently implement n-gram language models with practically unlimited size n. This approach, which is used with synchronous back-off, allows us to distinguish between alternative sequences using large contexts. We also show that we can build this kind of models with additional information for each symbol, such as part-of-speech tags and dependency information. The approach can also be viewed as a collection of virtual k-testable automata. Once built, we can directly access the results of any k-testable automaton generated from the input training data. Synchronous back- off automatically identies the k-testable automaton with the largest feasible k. We have used this approach in several classification tasks.

Abstract

Within scientific institutes there exist many language resources. These resources are often quite specialized and relatively unknown. The current infrastructural initiatives try to tackle this issue by collecting metadata about the resources and establishing centers with stable repositories to ensure the availability of the resources. It would be beneficial if the researcher could, by means of a simple query, determine which resources and which centers contain information useful to his or her research, or even work on a set of distributed resources as a virtual corpus. In this article we propose an architecture for a distributed search environment allowing researchers to perform searches in a set of distributed language resources.

Abstract

Finding regularities in large data sets requires implementations of systems that are efficient in both time and space requirements. Here, we describe a newly developed system that exploits the internal structure of the enhanced suffixarray to find significant patterns in a large collection of sequences. The system searches exhaustively for all significantly compressing patterns where patterns may consist of symbols and skips or wildcards. We demonstrate a possible application of the system by detecting interesting patterns in a Dutch and an English corpus.

Abstract

The problem of identifying and correcting confusibles, i.e. context-sensitive spelling errors, in text is typically tackled using specifically trained machine learning classifiers. For each different set of confusibles, a specific classifier is trained and tuned. In this research, we investigate a more generic approach to context-sensitive confusible correction. Instead of using specific classifiers, we use one generic classifier based on a language model. This measures the likelihood of sentences with different possible solutions of a confusible in place. The advantage of this approach is that all confusible sets are handled by a single model. Preliminary results show that the performance of the generic classifier approach is only slightly worse that that of the specific classifier approach

Abstract

In the context of confusible disambiguation (spelling correction that requires context), the synchronous back-off strategy combined with traditional n-gram language models performs well. However, when alternatives consist of a different number of tokens, this classification technique cannot be applied directly, because the computation of the probabilities is skewed. Previous work already showed that probabilities based on different order n-grams should not be compared directly. In this article, we propose new probability metrics in which the size of the n is varied according to the number of tokens of the confusible alternative. This requires access to n-grams of variable length. Results show that the synchronous back-off method is extremely robust. We discuss the use of suffix trees as a technique to store variable length n-gram information efficiently.

Abstract

In this article, we propose the use of suffix arrays to implement n-gram language models with practically unlimited size n. These unbounded n-grams are called 1-grams. This approach allows us to use large contexts efficiently to distinguish between different alternative sequences while applying synchronous back-off. From a practical point of view, the approach has been applied within the context of spelling confusibles, verb and noun agreement and prenominal adjective ordering. These initial experiments show promising results and we relate the performance to the size of the n-grams used for disambiguation.

Abstract

Listeners can make perceptual adjustments to phoneme categories in response to a talker who consistently produces a specific phoneme ambiguously. We investigate here whether this type of perceptual learning is also used to adapt to regional accent differences. Listeners were exposed to words produced by a Flemish talker whose realization of [x℄or [h℄ was ambiguous (producing [x℄like [h℄is a property of the West-Flanders regional accent). Before and after exposure they categorized a [x℄-[h℄continuum. For both Dutch and Flemish listeners there was no shift of the categorization boundary after exposure to ambiguous sounds in [x℄- or [h℄-biasing contexts. The absence of a lexically-driven learning effect for this contrast may be because [h℄is strongly influenced by coarticulation. As is not stable across contexts, it may be futile to adapt its representation when new realizations are heard

Abstract

This paper describes ongoing research aiming at the description of variation in speech as represented by asynchronous articulatory features. We will first illustrate how distances in the articulatory feature space can be used for event detection along speech trajectories in this space. The temporal structure imposed by the cosine distance in articulatory feature space coincides to a large extent with the manual segmentation on phone level. The analysis also indicates that the articulatory feature representation provides better such alignments than the MFCC representation does. Secondly, we will present first results that indicate that articulatory features can be used to probe for acoustic differences in the onsets of Dutch singulars and plurals.

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.

Abstract

This paper builds on previous work that aims at unraveling the structure of the speech signal by means of using probabilistic representations. The context of this work is a multi-pass speech recognition system in which a phone lattice is created and used as a basis for a lexical search in which symbolic mismatches are allowed at certain costs. The focus is on the optimization of the costs of phone insertions, deletions and substitutions that are used in the lexical decoding pass. Two optimization approaches are presented, one related to a multi-pass computational model for human speech recognition, the other based on a decoding in which Bayes’ risks are minimized. In the final section, the advantages of these optimization methods are discussed and compared.

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.

Abstract

Classical phonetic studies have shown that acoustic-articulatory cues can be interchanged without affecting the resulting phoneme percept (‘cue trading’). Cue trading has so far mainly been investigated in the context of phoneme identification. In this study, we investigate cue trading in word recognition, because words are the units of speech through which we communicate. This paper aims to provide a method to quantify cue trading effects by using a computational model of human word recognition. This model takes the acoustic signal as input and represents speech using articulatory feature streams. Importantly, it allows cue trading and underspecification. Its set-up is inspired by the functionality of Fine-Tracker, a recent computational model of human word recognition. This approach makes it possible, for the first time, to quantify cue trading in terms of a trade-off between features and to investigate cue trading in the context of a word recognition task.

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

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

Abstract

The present study shows that [t] consonants are affected by probabilistic factors in a syllable-timed language as French, and in spontaneous as well as in journalistic speech. Study 1 showed a word bigram frequency effect in spontaneous French, but its exact nature depended on the corpus on which the probabilistic measures were based. Study 2 investigated journalistic speech and showed an effect of the joint frequency of the test word and its following word. We discuss the possibility that these probabilistic effects are due to the speaker’s planning of upcoming words, and to the speaker’s adaptation to the listener’s needs.

Abstract

This study investigates phrase-medial vowel devoicing in European French (e.g. /ty po/ [typo] 'you can'). Our spontaneous speech data confirm that French phrase-medial devoicing is a frequent phenomenon affecting high vowels preceded by voiceless consonants. We also found that devoicing is more frequent in temporally reduced and coarticulated vowels. Complete and partial devoicing were conditioned by the same variables (speech rate, consonant type and distance from the end of the AP). Given these results, we propose that phrase-medial vowel devoicing in French arises mainly from the temporal compression of vocalic gestures and the aerodynamic conditions imposed by high vowels.

Abstract

This article describes the preparation, recording and orthographic transcription of a new speech corpus, the Nijmegen Corpus of Casual Spanish (NCCSp). The corpus contains around 30 hours of recordings of 52 Madrid Spanish speakers engaged in conversations with friends. Casual speech was elicited during three different parts, which together provided around ninety minutes of speech from every group of speakers. While Parts 1 and 2 did not require participants to perform any specific task, in Part 3 participants negotiated a common answer to general questions about society. Information about how to obtain a copy of the corpus can be found online at http://mirjamernestus.ruhosting.nl/Ernestus/NCCSp

Abstract

In situated communication, reference to an entity in the shared visual context can be established using eitheranexpression that conveys precise (minimally specified) or redundant (over-specified) information. There is, however, along-lasting debate in psycholinguistics concerningwhether the latter hinders referential processing. We present evidence from an eyetrackingexperiment recordingfixations as well asthe Index of Cognitive Activity –a novel measure of cognitive workload –supporting the view that over-specifications facilitate processing. We further present originalevidence that, above and beyond the effect of specificity,referring expressions thatuniformly reduce referential entropyalso benefitprocessing

Abstract

We investigated whether non-native listeners can exploit phonetic detail in recognizing potentially ambiguous utterances, as native listeners can [6, 7, 8, 9, 10]. Due to the phenomenon of intrusive /r/, the English phrase extra ice may sound like extra rice. A production study indicates that the intrusive /r/ can be distinguished from the onset /r/ in rice, as it is phonetically weaker. In two cross-modal identity priming studies, however, we found no conclusive evidence that Dutch learners of English are able to make use of this difference. Instead, auditory primes such as extra rice and extra ice with onset and intrusive /r/s activate both types of targets such as ice and rice. This supports the notion of spurious lexical activation in L2 perception.

Abstract

Every language manifests casual speech processes, and hence every second language too. This study examined how listeners deal with second-language casual speech processes, as a function of the processes in their native language. We compared a match case, where a second-language process t/-reduction) is also operative in native speech, with a mismatch case, where a second-language process (/r/-insertion) is absent from native speech. In each case native and non-native listeners judged stimuli in which a given phoneme (in sentence context) varied along a continuum from absent to present. Second-language listeners in general mimicked native performance in the match case, but deviated significantly from native performance in the mismatch case. Together these results make it clear that the mapping from first to second language is as important in the interpretation of casual speech processes as in other dimensions of speech perception. Unfamiliar casual speech processes are difficult to adapt to in a second language. Casual speech processes that are already familiar from native speech, however, are easy to adapt to; indeed, our results even suggest that it is possible for subtle difference in their occurrence patterns across the two languages to be detected,and to be accommodated to in second-language listening.

Abstract

This paper represents a pilot investigation of primed accentuation patterns produced by advanced Dutch speakers of Italian as a second language (L2). Contrastive accent patterns within prepositional phrases were elicited in a semispontaneous dialogue entertained with a confederate native speaker of Italian. The aim of the analysis was to compare learner’s contrastive accentual configurations induced by the confederate speaker’s prime against those produced by Italian and Dutch natives in the same testing conditions. F0 and speech rate data were analysed by applying powerful datadriven techniques available in the Functional Data Analysis statistical framework. Results reveal different accentual configurations in L1 and L2 Italian in response to the confederate’s prime. We conclude that learner’s accentual patterns mirror those ones produced by their L1 control group (prosodic-transfer hypothesis) although the hypothesis of a transient priming effect on learners’ choice of contrastive patterns cannot be completely ruled out.

Abstract

A dominant hypothesis in empirical research on the evolution of language is the following: the fundamental difference between animal and human communication systems is captured by the distinction between regular and more complex non-regular grammars. Studies reporting successful artificial grammar learning of nested recursive structures and imaging studies of the same have methodological shortcomings since they typically allow explicit problem solving strategies and this has been shown to account for the learning effect in subsequent behavioral studies. The present study overcomes these shortcomings by using subtle violations of agreement structure in a preference classification task. In contrast to the studies conducted so far, we use an implicit learning paradigm, allowing the time needed for both abstraction processes and consolidation to take place. Our results demonstrate robust implicit learning of recursively embedded structures (context-free grammar) and recursive structures with cross-dependencies (context-sensitive grammar) in an artificial grammar learning task spanning 9 days. Keywords: Implicit artificial grammar learning; centre embedded; cross-dependency; implicit learning; context-sensitive grammar; context-free grammar; regular grammar; non-regular grammar

Abstract

The task of automatic playlist continuation is generating a list of recommended tracks that can be added to an existing playlist. By suggesting appropriate tracks, i. e., songs to add to a playlist, a recommender system can increase the user engagement by making playlist creation easier, as well as extending listening beyond the end of current playlist. The ACM Recommender Systems Challenge 2018 focuses on such task. Spotify released a dataset of playlists, which includes a large number of playlists and associated track listings. Given a set of playlists from which a number of tracks have been withheld, the goal is predicting the missing tracks in those playlists. We participated in the challenge as the team Unconscious Bias and, in this paper, we present our approach. We extend adversarial autoencoders to the problem of automatic playlist continuation. We show how multiple input modalities, such as the playlist titles as well as track titles, artists and albums, can be incorporated in the playlist continuation task.

Abstract

This paper describes a new flexible delexicalization method based on glottal excited parametric speech synthesis scheme. The system utilizes inverse filtered glottal flow and all-pole modelling of the vocal tract. The method provides a possibility to retain and manipulate all relevant prosodic features of any kind of speech. Most importantly, the features include voice quality, which has not been properly modeled in earlier delexicalization methods. The functionality of the new method was tested in a prosodic tagging experiment aimed at providing word prominence data for a text-to-speech synthesis system. The experiment confirmed the usefulness of the method and further corroborated earlier evidence that linguistic factors influence the perception of prosodic prominence.

Abstract

The present study compared the role of metrical stress in comprehension and production of three-year-old children with a familial risk of dyslexia with that of normally developing children. A visual fixation task with stress (mis-)matches in bisyllabic words, as well as a non-word repetition task with bisyllabic targets were presented to the control and at-risk children. Results show that the at-risk group is less sensitive to stress mismatches in word recognition than the control group. Correct production of metrical stress patterns did not differ significantly between the groups, but the percentages of phonemes produced correctly were lower for the at-risk than the control group. The findings indicate that processing of metrical stress patterns is not impaired in at-risk children, but that the at-risk group cannot exploit metrical stress in word recognition