Publications

Abstract

The notion of relational grammar is extented to ternary relations and illustrated by a fragment of English. Some of Peirce's terms for ternary relations are shown to be incorrect and corrected.

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

A distinction between strong and weak vowels can be drawn on the basis of vowel quality, of stress, or of both factors. An experiment was conducted in which sets of contextually matched word-intial vowels ranging from clearly strong to clearly weak were cross-spliced, and the naturalness of the resulting words was rated by listeners. The ratings showed that in general cross-spliced words were only significantly less acceptable than unspliced words when schwa was not involved; this supports a categorical distinction based on vowel quality.

Abstract

One of a listener's major tasks in understanding continuous speech is segmenting the speech signal into separate words. When listening conditions are difficult, speakers can help listeners by deliberately speaking more clearly. In three experiments, we examined how word boundaries are produced in deliberately clear speech. We found that speakers do indeed attempt to mark word boundaries; moreover, they differentiate between word boundaries in a way which suggests they are sensitive to listener needs. Application of heuristic segmentation strategies makes word boundaries before strong syllables easiest for listeners to perceive; but under difficult listening conditions speakers pay more attention to marking word boundaries before weak syllables, i.e. they mark those boundaries which are otherwise particularly hard to perceive.

Abstract

Speakers and listeners have a shared goal: to communicate. The processes of speech perception and of speech production interact in many ways under the constraints of this communicative goal; such interaction is as characteristic of prosodic processing as of the processing of other aspects of linguistic structure. Two of the major uses of prosodic information in situations of communication are to encode salience and segmentation, and these themes unite the contributions to the symposium introduced by the present review.

Abstract

Dutch listeners were slower to make judgements about the semantic relatedness between a spoken target word (e.g. atLEET, 'athlete') and a previously presented visual prime word (e.g. SPORT 'sport') when the spoken word was mis-stressed. The adverse effect of mis-stressing confirms the role of stress information in lexical recognition in Dutch. However, although the erroneous stress pattern was always initially compatible with a competing word (e.g. ATlas, 'atlas'), mis-stressed words did not produced high false alarm rates in unrelated pairs (e.g. SPORT - atLAS). This suggests that stress information did not completely rule out segmentally matching but suprasegmentally mismatching words, a finding consistent with spoken-word recognition models involving multiple activation and inter-word competition.

Abstract

Simulations explored the inability of the TRACE model of spoken-word recognition to model the effects on human listening of acoustic-phonetic mismatches in word forms. The source of TRACE's failure lay not in its interactive connectivity, not in the presence of interword competition, and not in the use of phonemic representations, but in the need for continuously optimised interpretation of the input. When an analogue of TRACE was allowed to cycle to asymptote on every slice of input, an acceptable simulation of the subcategorical mismatch data was achieved. Even then, however, the simulation was not as close as that produced by the Merge model.

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

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

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

Three groups of monolingual listeners, with Standard Chinese, Dutch and Hungarian as their native language, judged pairs of trisyllabic stimuli which differed only in their itch pattern. The segmental structure of the stimuli was made up by the experimenters and presented to subjects as being taken from a little-known language spoken on a South Pacific island. Pitch patterns consisted of a single rise-fall located on or near the second syllable. By and large, listeners selected the stimulus with the higher peak, the later eak, and the higher end rise as the one that signalled a question, regardless of language group. The result is argued to reflect innate, non-linguistic knowledge of the meaning of pitch variation, notably Ohala’s Frequency Code. A significant difference between groups is explained as due to the influence of the mother tongue.

Abstract

This paper investigates the time and space complexity of word order computation in the psycholinguistically motivated grammar formalism of Performance Grammar (PG). In PG, the first stage of syntax assembly yields an unordered tree ('mobile') consisting of a hierarchy of lexical frames (lexically anchored elementary trees). Associated with each lexica l frame is a linearizer—a Finite-State Automaton that locally computes the left-to-right order of the branches of the frame. Linearization takes place after the promotion component may have raised certain constituents (e.g. Wh- or focused phrases) into the domain of lexical frames higher up in the syntactic mobile. We show that the worst-case time and space complexity of analyzing input strings of length n is O(n5) and O(n4), respectively. This result compares favorably with the time complexity of word-order computations in Tree Adjoining Grammar (TAG). A comparison with Head-Driven Phrase Structure Grammar (HPSG) reveals that PG yields a more declarative linearization method, provided that the FSA is rewritten as an equivalent regular expression.

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

n this study we investigated the durational correlates of lexical stress and pitch accent at normal and fast speech rate in Dutch. Previous literature on English shows that durations of lexically unstressed vowels are reduced more than stressed vowels when speakers increase their speech rate. We found that the same holds for Dutch, irrespective of whether the unstressed vowel is schwa or a "full" vowel. In the same line, we expected that vowels in words without a pitch accent would be shortened relatively more than vowels in words with a pitch accent. This was not the case: if anything, the accented vowels were shortened relatively more than the unaccented vowels. We conclude that duration is an important cue for lexical stress, but not for pitch accent.

Abstract

Studies on fast speech have shown that word-level timing of fast speech differs from that of normal rate speech in that unstressed syllables are shortened more than stressed syllables as speech rate increases. An earlier experiment showed that the intelligibility of time-compressed speech could not be improved by making its temporal organisation closer to natural fast speech. To test the hypothesis that segmental intelligibility is more important than prosodic timing in listening to timecompressed speech, the intelligibility of bisyllabic words was tested in three time-compression conditions: either stressed and unstressed syllable were compressed to the same degree, or the stressed syllable was compressed more than the unstressed syllable, or the reverse. As was found before, imitating wordlevel timing of fast speech did not improve intelligibility over linear compression. However, the results did not confirm the hypothesis either: there was no difference in intelligibility between the three compression conditions. We conclude that segmental intelligibility plays an important role, but further research is necessary to decide between the contributions of prosody and segmental intelligibility to the word-level intelligibility of time-compressed speech.

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

Words can be distinguished by segmental differences or by suprasegmental differences or both. Studies from English suggest that suprasegmentals play little role in human spoken-word recognition; English stress, however, is nearly always unambiguously coded in segmental structure (vowel quality); this relationship is less close in Dutch. The present study directly compared the effects of segmental and suprasegmental mispronunciation on word recognition in Dutch. There was a strong effect of suprasegmental mispronunciation, suggesting that Dutch listeners do exploit suprasegmental information in word recognition. Previous findings indicating the effects of mis-stressing for Dutch differ with stress position were replicated only when segmental change was involved, suggesting that this is an effect of segmental rather than suprasegmental processing.

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

A recurrently connected attractor neural network with a Hebbian learning rule is currently our best ANN analogy for a piece cortex. Functionally biological memory operates on a spectrum of time scales with regard to induction and retention, and it is modulated in complex ways by sub-cortical neuromodulatory systems. Moreover, biological memory networks are commonly believed to be highly distributed and engage many co-operating cortical areas. Here we focus on the temporal aspects of induction and retention of memory in a connectionist type attractor memory model of a piece of cortex. A continuous time, forgetful Bayesian-Hebbian learning rule is described and compared to the characteristics of LTP and LTD seen experimentally. More generally, an attractor network implementing this learning rule can operate as a long-term, intermediate-term, or short-term memory. Modulation of the print-now signal of the learning rule replicates some experimental memory phenomena, like e.g. the von Restorff effect.

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

Lexical knowledge influences how human listeners make decisions about speech sounds. Positive lexical effects (faster responses to target sounds in words than in nonwords) are robust across several laboratory tasks, while negative effects (slower responses to targets in more word-like nonwords than in less word-like nonwords) have been found in phonetic decision tasks but not phoneme monitoring tasks. The present experiments tested whether negative lexical effects are therefore a task-specific consequence of the forced choice required in phonetic decision. We compared phoneme monitoring and phonetic decision performance using the same Dutch materials in each task. In both experiments there were positive lexical effects, but no negative lexical effects. We observe that in all studies showing negative lexical effects, the materials were made by cross-splicing, which meant that they contained perceptual evidence supporting the lexically-consistent phonemes. Lexical knowledge seems to influence phonemic decision-making only when there is evidence for the lexically-consistent phoneme in the speech signal.

Abstract

We briefly describe the Merge model of phonemic decision-making, and, in the light of general arguments about the possible role of feedback in spoken-word recognition, defend Merge's feedforward structure. Merge not only accounts adequately for the data, without invoking feedback connections, but does so in a parsimonious manner.

Abstract

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

Abstract

Gaze cues play an important role in human communication and are used to coordinate turn-taking and joint attention, as well as to regulate intimacy. In order to have fluent conversations with people, social robots need to exhibit humanlike gaze behavior. Previous Gaze Control Systems (GCS) in HRI have automated robot gaze using data-driven or heuristic approaches. However, these systems tend to be mainly reactive in nature. Planning the robot gaze ahead of time could help in achieving more realistic gaze behavior and better eye-head coordination. In this paper, we propose and implement a novel planning-based GCS. We evaluate our system in a comparative within-subjects user study (N=26) between a reactive system and our proposed system. The results show that the users preferred the proposed system and that it was significantly more interpretable and better at regulating intimacy.

Abstract

Two word-spotting experiments are reported that examine whether the Possible-Word Constraint (PWC) [1] is a language-specific or language-universal strategy for the segmentation of continuous speech. The PWC disfavours parses which leave an impossible residue between the end of a candidate word and a known boundary. The experiments examined cases where the residue was either a CV syllable with a lax vowel, or a CVC syllable with a schwa. Although neither syllable context is a possible word in English, word-spotting in both contexts was easier than with a context consisting of a single consonant. The PWC appears to be language-universal rather than language-specific.

Abstract

Simulations explored the inability of the TRACE model of spoken-word recognition to model the effects on human listening of subcategorical mismatch in word forms. The source of TRACE's failure lay not in interactive connectivity, not in the presence of inter-word competition, and not in the use of phonemic representations, but in the need for continuously optimised interpretation of the input. When an analogue of TRACE was allowed to cycle to asymptote on every slice of input, an acceptable simulation of the subcategorical mismatch data was achieved. Even then, however, the simulation was not as close as that produced by the Merge model, which has inter-word competition, phonemic representations and continuous optimisation (but no interactive connectivity).

Abstract

A database is presented of relative familiarity ratings for 24 sets of Japanese words, each set comprising words overlapping in the initial portions. These ratings are useful for the generation of material sets for research in the recognition of spoken words.

Abstract

Dutch and Spanish differ in how predictable the stress pattern is as a function of the segmental content: it is correlated with syllable weight in Dutch but not in Spanish. In the present study, two experiments were run to compare the abilities of Dutch and Spanish speakers to separately process segmental and stress information. It was predicted that the Spanish speakers would have more difficulty focusing on the segments and ignoring the stress pattern than the Dutch speakers. The task was a speeded classification task on CVCV syllables, with blocks of trials in which the stress pattern could vary versus blocks in which it was fixed. First, we found interference due to stress variability in both languages, suggesting that the processing of segmental information cannot be performed independently of stress. Second, the effect was larger for Spanish than for Dutch, suggesting that that the degree of interference from stress variation may be partially mitigated by the predictability of stress placement in the language.

Abstract

Recent FMRI studies indicate that language related brain regions are engaged in artificial grammar (AG) processing. In the present study we investigate the Reber grammar by means of formal analysis and network simulations. We outline a new method for describing the network dynamics and propose an approach to grammar extraction based on the state-space dynamics of the network. We conclude that statistical frequency-based and rule-based acquisition procedures can be viewed as complementary perspectives on grammar learning, and more generally, that classical cognitive models can be viewed as a special case of a dynamical systems perspective on information processing

Abstract

A series of experiment tested Ekman’s (1992) hypothesis that there are a set of positive basic emotions that are expressed using vocal para-linguistic sounds, e.g. laughter and cheers. The proposed categories investigated were amusement, contentment, pleasure, relief and triumph. Behavioural testing using a forced-choice task indicated that participants were able to reliably recognize vocal expressions of the proposed emotions. A cross-cultural study in the preliterate Himba culture in Namibia confirmed that these categories are also recognized across cultures. A recognition test of acoustically manipulated emotional vocalizations established that the recognition of different emotions utilizes different vocal cues, and that these in turn differ from the cues used when comprehending speech. In a study using fMRI we found that relative to a signal correlated noise baseline, the paralinguistic expressions of emotion activated bilateral superior temporal gyri and sulci, lateral and anterior to primary auditory cortex, which is consistent with the processing of non linguistic vocal cues in the auditory ‘what’ pathway. Notably amusement was associated with greater activation extending into both temporal poles and amygdale and insular cortex. Overall, these results support the claim that ‘happiness’ can be fractionated into amusement, pleasure, relief and triumph.

Abstract

This paper addresses the issue of large-vocabulary recognition in a specific word class. We propose a two-pass strategy in which only major cities are explicitly represented in the first stage lexicon. An unknown word model encoded as a phone loop is used to detect OOV city names (referred to as rare city names). After which SpeM, a tool that can extract words and word-initial cohorts from phone graphs on the basis of a large fallback lexicon, provides an N-best list of promising city names on the basis of the phone sequences generated in the first stage. This N-best list is then inserted into the second stage lexicon for a subsequent recognition pass. Experiments were conducted on a set of spontaneous telephone-quality utterances each containing one rare city name. We tested the size of the N-best list and three types of language models (LMs). The experiments showed that SpeM was able to include nearly 85% of the correct city names into an N-best list of 3000 city names when a unigram LM, which also boosted the unigram scores of a city name in a given state, was used.

Abstract

This work focuses on efficient use of the training material by selecting the optimal set of model topologies. We do this by training multiple word models of each word class, based on a subclassification according to a priori knowledge of the training material. We will examine classification criteria with respect to duration of the word, gender of the speaker, position of the word in the utterance, pauses in the vicinity of the word, and combinations of these. Comparative experiments were carried out on a corpus consisting of Dutch spoken connected digit strings and isolated digits, which are recorded in a wide variety of acoustic conditions. The results show, that classification based on gender of the speaker, position of the digit in the string, pauses in the vicinity of the training tokens, and models based on a combination of these criteria perform significantly better than the set with single models per digit.

Abstract

In this paper, we illustrate the close parallels between the research fields of human speech recognition (HSR) and automatic speech recognition (ASR) using a computational model of human word recognition, SpeM, which was built using techniques from ASR. We show that ASR has proven to be useful for improving models of HSR by relieving them of some of their shortcomings. However, in order to build an integrated computational model of all aspects of HSR, a lot of issues remain to be resolved. In this process, ASR algorithms and techniques definitely can play an important role.

Abstract

We present DiscoGeM, a crowdsourced corpus of 6,505 implicit discourse relations from three genres: political speech,
literature, and encyclopedic texts. Each instance was annotated by 10 crowd workers. Various label aggregation methods
were explored to evaluate how to obtain a label that best captures the meaning inferred by the crowd annotators. The results
show that a significant proportion of discourse relations in DiscoGeM are ambiguous and can express multiple relation senses.
Probability distribution labels better capture these interpretations than single labels. Further, the results emphasize that text
genre crucially affects the distribution of discourse relations, suggesting that genre should be included as a factor in automatic
relation classification. We make available the newly created DiscoGeM corpus, as well as the dataset with all annotator-level
labels. Both the corpus and the dataset can facilitate a multitude of applications and research purposes, for example to
function as training data to improve the performance of automatic discourse relation parsers, as well as facilitate research into
non-connective signals of discourse relations.

Abstract

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

Abstract

This paper investigates the interaction between acoustic scores and symbolic mismatch penalties in multi-pass speech decoding techniques that are based on the creation of a segment graph followed by a lexical search. The interaction between acoustic and symbolic mismatches determines to a large extent the structure of the search space of these multipass approaches. The background of this study is a recently developed computational model of human word recognition, called SpeM. SpeM is able to simulate human word recognition data and is built as a multi-pass speech decoder. Here, we focus on unravelling the structure of the search space that is used in SpeM and similar decoding strategies. Finally, we elaborate on the close relation between distances in this search space, and distance measures in search spaces that are based on a combination of acoustic and phonetic features.

Abstract

Machine learning models of visual action recognition are typically trained and tested on data from specific situations where actions are associated with certain objects. It is an open question how action-object associations in the training set influence a model's ability to generalize beyond trained situations. We set out to identify properties of training data that lead to action recognition models with greater generalization ability. To do this, we take inspiration from a cognitive mechanism called cross-situational learning, which states that human learners extract the meaning of concepts by observing instances of the same concept across different situations. We perform controlled experiments with various types of action-object associations, and identify key properties of action-object co-occurrence in training data that lead to better classifiers. Given that these properties are missing in the datasets that are typically used to train action classifiers in the computer vision literature, our work provides useful insights on how we should best construct datasets for efficiently training for better generalization.