Publications

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

Abstract

In Yukatek Maya, event types are lexicalized in verb roots and stems that fall into a number of different form classes on the basis of (a) patterns of aspect-mood marking and (b) priviledges of undergoing valence-changing operations. Of particular interest are the intransitive classes in the light of Perlmutter’s (1978) Unaccusativity hypothesis. In the spirit of Levin & Rappaport Hovav (1995) [L&RH], Van Valin (1990), Zaenen (1993), and others, this paper investigates whether (and to what extent) the association between formal predicate classes and event types is determined by argument structure features such as ‘agentivity’ and ‘control’ or features of lexical aspect such as ‘telicity’ and ‘durativity’. It is shown that mismatches between agentivity/control and telicity/durativity are even more extensive in Yukatek than they are in English (Abusch 1985; L&RH, Van Valin & LaPolla 1997), providing new evidence against Dowty’s (1979) reconstruction of Vendler’s (1967) ‘time schemata of verbs’ in terms of argument structure configurations. Moreover, contrary to what has been claimed in earlier studies of Yukatek (Krämer & Wunderlich 1999, Lucy 1994), neither agentivity/control nor telicity/durativity turn out to be good predictors of verb class membership. Instead, the patterns of aspect-mood marking prove to be sensitive only to the presence or absense of state change, in a way that supports the unified analysis of all verbs of gradual change proposed by Kennedy & Levin (2001). The presence or absence of ‘internal causation’ (L&RH) may motivate the semantic interpretation of transitivization operations. An explicit semantics for the valence-changing operations is proposed, based on Parsons’s (1990) Neo-Davidsonian approach.

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.

Abstract

Narrow focus refers to accent placement that forces one interpretation of a sentence, which is then often perceived contrastively. Narrow focus is formalised in terms of alternative sets, i.e. contextually or situationally salient alternatives. In this paper, we investigate whether this model is valid also in human utterance processing. We present an eye-tracking experiment to study listeners’ expectations (i.e. eye-movements) with respect to upcoming referents. Some of the objects contrast in colour with objects that were previously referred to, others do not; the objects are referred to with either a narrow focus on the colour adjective or with broad focus on the noun. Results show that narrow focus on the adjective increases early fixations to contrastive referents. Narrow focus hence activates alternative referents in human utterance processing

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.

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.

Abstract

The present study set out to pin down the role of four pitch accents, fall (H*L), rise-fall (L*HL), rise (L*H), fall-rise (H*LH), as well as deaccentuation, in interpreting new vs. given information in British English by the eyetracking paradigm. The pitch accents in question were claimed to convey information status in theories of English intonational meaning. There is, however, no consensus on the postulated roles of these pitch accents. Results clearly show that pitch accent type can and does matter when interpreting information status. The effects can be reflected in the mean proportions of fixations to the competitor in a selected time window. These patterns are also present in proportions of fixations to the target but to a lesser extent. Interestingly, the effects of pitch accent types are also reflected in how fast the participants could adjust their decision as to which picture to move before the name of the picture was fully revealed. For example, when the competitor was a given entity, the proportion of fixations to the competitor increased initially in most accent conditions in the first as a result of subjects' bias towards a given entity, but started to decrease substantially earlier in the H*L condition than in the L*H and deaccentuation conditions.

Abstract

This study investigates how Mandarin-speaking children interpret state-change verbs. In Mandarin, state-change is typically encoded with resultative verb compounds (RVCs), in which the first verb (V1) specifies an action and the second (V2) a result, for example, zhai-xia 'pick-descend' (= pick, pick off/down). Unlike English state-change verb such as pick, smash, mix and fill, the action verb (V1) may imply a state-change but it does not entail it; the state-change is specified by the additional result verb (V2). Previous studies have shown that children learning English and German tend to neglect the state-change meaning in monomorphemic state-change verbs like mix and fill (Gentner, 1978; Gropen et al, 1991) and verb-particle constructions like abplücken 'pick off' (Wittek, 1999, 2000) - they do not realize that this meaning is entailed. This study examines how Mandarin-speaking children interpret resultative verb compounds and the first verb of an RVC. Four groups of Mandarin-speaking children (mean ages 2;6, 3;6, 4;6, 6;1) and an adult group participated in a judgment task. The results show that Mandarin-speaking children know from a very young age that RVCs entail a state-change; ironically, however, they make a mistake that is just the opposite to that made by the learners of English and German: they often incorrectly interpret the action verb (V1) of an RVC as if it, in itself, also entails a state-change, even though it does not. This result suggests that children do not have a uniform strategy for interpreting verb meaning, but are influenced by the language-specific lexicalization patterns they encounter in their language.

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.

Abstract

We investigated how listeners of two unrelated languages, Dutch and Korean, process phonotactically legitimate and illegitimate sounds spoken in Dutch and American English. To Dutch listeners, unreleased word-final stops are phonotactically illegal because word-final stops in Dutch are generally released in isolation, but to Korean listeners, released final stops are illegal because word-final stops are never released in Korean. Two phoneme monitoring experiments showed a phonotactic effect: Dutch listeners detected released stops more rapidly than unreleased stops whereas the reverse was true for Korean listeners. Korean listeners with English stimuli detected released stops more accurately than unreleased stops, however, suggesting that acoustic-phonetic cues associated with released stops improve detection accuracy. We propose that in non-native speech perception, phonotactic legitimacy in the native language speeds up phoneme recognition, the richness of acousticphonetic cues improves listening accuracy, and familiarity with the non-native language modulates the relative influence of these two factors.

Abstract

The aim of this study was to determine if Dutch speakers reliably signal phrase-internal lexical boundaries, and if so, how. Six speakers recorded 4 pairs of phonemically identical strong-weak-strong (SWS) strings with matching syllable boundaries but mismatching intended word boundaries (e.g. reis # pastei versus reispas # tij, or more broadly C1V2(C)#C2V2(C)C3V3(C) vs. C1V2(C)C2V2(C)#C3V3(C)). An Analysis of Variance revealed 3 acoustic parameters that were significantly greater in S#WS items (C2 DURATION, RIME1 DURATION, C3 BURST AMPLITUDE) and 5 parameters that were significantly greater in the SW#S items (C2 VOT, C3 DURATION, RIME2 DURATION, RIME3 DURATION, and V2 AMPLITUDE). Additionally, center of gravity measurements suggested that the [s] to [t] coarticulation was greater in reis # pa[st]ei versus reispa[s] # [t]ij. Finally, a Logistic Regression Analysis revealed that the 3 parameters (RIME1 DURATION, RIME2 DURATION, and C3 DURATION) contributed most reliably to a S#WS versus SW#S classification.

Abstract

We report an investigation of the perception of American English phonemes by Dutch listeners proficient in English. Listeners identified either the consonant or the vowel in most possible English CV and VC syllables. The syllables were embedded in multispeaker babble at three signal-to-noise ratios (16 dB, 8 dB, and 0 dB). Effects of signal-to-noise ratio on vowel and consonant identification are discussed as a function of syllable position and of relationship to the native phoneme inventory. Comparison of the results with previously reported data from native listeners reveals that noise affected the responding of native and non-native listeners similarly.

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.

Abstract

Language-specific differences in the size and distribution of the phonemic repertoire can have implications for the task facing listeners in recognising spoken words. A language with more phonemes will allow shorter words and reduced embedding of short words within longer ones, decreasing the potential for spurious lexical competitors to be activated by speech signals. We demonstrate that this is the case via comparative analyses of the vocabularies of English and Spanish. A language which uses suprasegmental as well as segmental contrasts, however, can substantially reduce the extent of spurious embedding.

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.

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.

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.

Abstract

Two lexical decision experiments in Cantonese are described in which the recognition of spoken target words as a function of phonological similarity to a preceding prime is investigated. Phonological similaritv in first syllables produced inhibition, while similarity in second syllables led to facilitation. Differences between syllables in tonal and segmental structure had generally similar effects.

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.

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.

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.

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.

Abstract

In this paper we investigate the neural correlates of syntactic classification of an acquired grammatical sequence structure in an event-related FMRI study. During acquisition, participants were engaged in an implicit short-term memory task without performance feedback. We manipulated the statistical frequency-based and rule-based characteristics of the classification stimuli independently in order to investigate their role in artificial grammar acquisition. The participants performed reliably above chance on the classification task. We observed a partly overlapping corticostriatal processing network activated by both manipulations including inferior prefrontal, cingulate, inferior parietal regions, and the caudate nucleus. More specifically, the left inferior frontal BA 45 and the caudate nucleus were sensitive to syntactic violations and endorsement, respectively. In contrast, these structures were insensitive to the frequency-based manipulation.

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.

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.

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.

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.

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.

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.

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.

Abstract

This study investigates the time-course of information processing in both visual as well as in the auditory speech as used for word identification in face-to-face communication. It extends the limited previous research on this topic and provides a valuable database for future research in audiovisual speech perception. An evaluation of models of speech perception by ear and eye in their ability to account for the audiovisual gating data shows a superior role of the fuzzy logical model of perception (FLMP) [1] over additive models of perception. A new dynamic version of the FLMP seems to be a promising model to account for the complex interplay of perceptual and cognitive information in audiovisual spoken word recognition.

Abstract

Mutations of the epidermal growth factor receptor (EGFR) gene are found at a relatively high frequency in glioma, with the most common being the de2-7 EGFR (or EGFRvIII). This mutation arises from an in-frame deletion of exons 2–7, which removes 267 amino acids from the extracellular domain of the receptor. Despite being unable to bind ligand, the de2-7 EGFR is constitutively active at a low level. Transfection of human glioma cells with the de2-7 EGFR has little effect in vitro, but when grown as tumor xenografts this mutated receptor imparts a dramatic growth advantage. We have now mapped the phosphorylation pattern of de2-7 EGFR, both in vivo and in vitro, using a panel of antibodies unique to the different phosphorylated tyrosine residues. Phosphorylation of de2-7 EGFR was detected constitutively at all tyrosine sites surveyed both in vitro and in vivo, including tyrosine 845, a known target in the wild-type EGFR for src kinase. There was a substantial upregulation of phosphorylation at every tyrosine residue of the de2-7 EGFR when cells were grown in vivo compared to the receptor isolated from cells cultured in vitro. Upregulation of phosphorylation could be mimicked in vitro by the addition of specifi c components of the ECM such as collagen via an integrin-dependent mechanism. Since this increase in in vivo phosphorylation enhances de2-7 EGFR signaling, this observation explains why the growth enhancement mediated by de2-7 EGFR is largely restricted to the in vivo environment. In a second set of experiments we analyzed the interaction between EGFRvIII and ErbB2. Co-expression of these proteins in NR6 cells, a mouse fi broblast line devoid of ErbB family members, dramatically enhanced in vivo tumorigenicity of these cells compared to cells expressing either protein alone. Detailed analysis of these xenografts demonstrated that EGFRvIII could heterodimerize and transphosphorylate the ErbB2. Since both EGFRvIII and ErbB2 are commonly expressed at gliomas, this data suggests that the co-expression of these two proteins may enhance glioma tumorigenicity.

Abstract

Mutations of the epidermal growth factor receptor (EGFR) gene are found at a relatively high frequency in glioma, with the most common being the de2-7 EGFR (or EGFRvIII). This mutation arises from an in-frame deletion of exons 2-7, which removes 267 amino acids from the extracellular domain of the receptor. Despite being unable to bind ligand, the de2-7 EGFR is constitutively active at a low level. Transfection of human glioma cells with the de2-7 EGFR has little effect in vitro, but when grown as tumor xenografts this mutated receptor imparts a dramatic growth advantage. We mapped the phosphorylation pattern of de2-7 EGFR, both in vivo and in vitro, using a panel of antibodies specific for different phosphorylated tyrosine residues. Phosphorylation of de2-7 EGFR was detected constitutively at all tyrosine sites surveyed in vitro and in vivo, including tyrosine 845, a known target in the wild-type EGFR for src kinase. There was a substantial upregulation of phosphorylation at every yrosine residue of the de2-7 EGFR when cells were grown in vivo compared to the receptor isolated from cells cultured in vitro. Upregulation of phosphorylation at tyrosine 845 could be stimulated in vitro by the addition of specific components of the ECM via an integrindependent mechanism. These observations may partially explain why the growth enhancement mediated by de2-7 EGFR is largely restricted to the in vivo environment

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

Abstract

This paper examines the language-specific aspect of the TIME PASSING IS MOTION metaphor and suggests that the temporal construal of time can be influenced by a person's second language. Ahrens and Huang (2002) have analyzed the source domain of MOTION for the TIME metaphor into two special cases. In the special case one, TIME PASSING is an object that moves towards an ego. For example, qimuokao kuai dao le "the final exam is approaching." In the special case two, TIME PASSING is a point (that a plural ego is attached to) that moves across a landscape. For example, women kuai dao qimuokao le "we are approaching the final exam." In addition, in English, the ego in the special case one faces the future while in Chinese, the ego faces the past. The current experiment hypothesizes that English influences the choice of the orientation of the ego in native Chinese speakers who speak English as the second language. 54 subjects are asked to switch the clock time one hour forward. Results show that native Chinese speakers living in the Chinese speaking country tend to move the clock one hour forward to the past (92%) while native Chinese speakers living in an English speaking country are less likely to do so (60%). This implies that the experience of English influences the conceptualization of time in Mandarin Chinese.

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.

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.

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.

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.

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.

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%.