Publications

Abstract

To achieve true interoperability for valuable linguistic resources different levels of variation need to be addressed. ISO Technical Committee 37, Terminology and other language and content resources, is developing a Data Category Registry. This registry will provide a reusable set of data categories. A new implementation, dubbed ISOcat, of the registry is currently under construction. This paper shortly describes the new data model for data categories that will be introduced in this implementation. It goes on with a sketch of the standardization process. Completed data categories can be reused by the community. This is done by either making a selection of data categories using the ISOcat web interface, or by other tools which interact with the ISOcat system using one of its various Application Programming Interfaces. Linguistic resources that use data categories from the registry should include persistent references, e.g. in the metadata or schemata of the resource, which point back to their origin. These data category references can then be used to determine if two or more resources share common semantics, thus providing a level of interoperability close to the source data and a promising layer for semantic alignment on higher levels

Abstract

Spatial terms in the world’s languages appear to reflect both universal conceptual tendencies and linguistic convention. A similarly mixed picture in the case of color naming has been accounted for in terms of near-optimal partitions of color space. Here, we demonstrate that this account generalizes to spatial terms. We show that the spatial terms of 9 diverse languages near-optimally partition a similarity space of spatial meanings, just as color terms near-optimally partition color space. This account accommodates both universal tendencies and cross-language differences in spatial category extension, and identifies general structuring principles that appear to operate across different semantic domains.

Abstract

The previous literature has suggested that the hand movement in co-speech gestures and signs consists of a series of phases with qualitatively different dynamic characteristics. In this paper, we propose a syntagmatic rule system for movement phases that applies to both co-speech gestures and signs. Descriptive criteria for the rule system were developed for the analysis video-recorded continuous production of signs and gesture. It involves segmenting a stream of body movement into phases and identifying different phase types. Two human coders used the criteria to analyze signs and cospeech gestures that are produced in natural discourse. It was found that the criteria yielded good inter-coder reliability. These criteria can be used for the technology of automatic recognition of signs and co-speech gestures in order to segment continuous production and identify the potentially meaningbearing phase.

Abstract

The Max Planck Institute for Psycholinguistics (MPI) manages an archive of linguistic research data with a current size of almost 20 Terabytes. Apart from in-house researchers other projects also store their data in the archive, most notably the Documentation of Endangered Languages (DoBeS) projects. The archive is available online and can be accessed by anybody with Internet access. To be able to manage this large amount of data the MPI's technical group has developed a software suite called Language Archiving Technology (LAT) that on the one hand helps researchers and archive managers to manage the data and on the other hand helps users in enriching their primary data with additional layers. All the MPI software is Java-based and developed according to open source principles (GNU, 2007). All three major operating systems (Windows, Linux, MacOS) are supported and the software works similarly on all of them. As the archive is online, many of the tools, especially the ones for accessing the data, are browser based. Some of these browser-based tools make use of Adobe Flex to create nice-looking GUIs. The LAT suite is a complete set of management and enrichment tools, and given the interaction between the tools the result is a complete LAT software domain. Over the last 10 years, this domain has proven its functionality and use, and is being deployed to servers in other institutions. This deployment is an important step in getting the archived resources back to the members of the speech communities whose languages are documented. In the paper we give an overview of the tools of the LAT suite and we describe their functionality and role in the integrated process of archiving, management and enrichment of linguistic data.

Abstract

Individual and interactive movement behaviour (non-verbal behaviour / communication) specifically reflects implicit processes in psychotherapy [1,4,11]. However, thus far, the registration of movement behaviour has been a methodological challenge. We will present a coding system combined with an annotation tool for the analysis of movement behaviour during psychotherapy interviews [9]. The NGCS coding system enables to classify body movements based on their kinetic features alone [5,7]. The theoretical assumption behind the NGCS is that its main kinetic and functional movement categories are differentially associated with specific psychological functions and thus, have different neurobiological correlates [5-8]. ELAN is a multimodal annotation tool for digital video media [2,3,12]. The NGCS / ELAN template enables to link any movie to the same coding system and to have different raters independently work on the same file. The potential of movement behaviour analysis as an objective tool for psychotherapy research and for supervision in the psychosomatic practice is discussed by giving examples of the NGCS/ELAN analyses of psychotherapy sessions. While the quality of kinetic turn-taking and the therapistrsquor;s (implicit) adoption of the patientrsquor;s movements may predict therapy outcome, changes in the patientrsquor;s movement behaviour pattern may indicate changes in cognitive concepts and emotional states and thus, may help to identify therapeutically relevant processes [10].

Abstract

Using real-time eye-movement measures, we asked how a fantastical discourse context competes with stored representations of semantic and world knowledge to influence children's and adults' moment-by-moment interpretation of a story. Seven-year- olds were less effective at bypassing stored semantic and world knowledge during real-time interpretation than adults. Nevertheless, an effect of discourse context on comprehension was still apparent.

Abstract

This paper presents a novel model for 3D image segmentation and reconstruction. It has been designed with the aim to be implemented over a computer cluster or a multi-core platform. The required features include a nearly absolute independence between the processes participating in the segmentation task and providing amount of work as equal as possible for all the participants. As a result, it is avoid many drawbacks often encountered when performing a parallelization of an algorithm that was constructed to operate in a sequential manner. Furthermore, the proposed algorithm based on the new segmentation model is efficient and shows a very good, nearly linear performance growth along with the growing number of processing units.

Abstract

Digital processing of medical images has helped physicians and patients during past years by allowing examination and diagnosis on a very precise level. Nowadays possibly the biggest deal of support it can offer for modern healthcare is the use of high performance computing architectures to treat the huge amounts of data that can be collected by modern acquisition devices. This paper presents a parallel processing implementation of an image segmentation algorithm that operates on a computer cluster equipped with 10 processing units. Thanks to well-organized distribution of the workload we manage to significantly shorten the execution time of the developed algorithm and reach a performance gain very close to linear.

Abstract

Deformable models are a popular family of image segmentation techniques, which has been gaining significant focus in the last two decades, serving both for real-world applications as well as the base for research work. One of the features that the deformable models offer and that is considered a much desired one, is the ability to change their topology during the segmentation process. Using this characteristic it is possible to perform segmentation of objects with discontinuities in their bodies or to detect an undefined number of objects in the scene. In this paper we present our model for handling the topology changes in image segmentation methods based on the Active Volumes solution. The said model is capable of performing the changes in the structure of objects while the segmentation progresses, what makes it efficient and suitable for implementations over powerful execution environment, like multi-core architectures or computer clusters.

Abstract

In this paper we present a novel approach for image segmentation using Active Nets and Active Volumes. Those solutions are based on the Deformable Models, with slight difference in the method for describing the shapes of interests - instead of using a contour or a surface they represented the segmented objects with a mesh structure, which allows to describe not only the surface of the objects but also to model their interiors. This is obtained by dividing the nodes of the mesh in two categories, namely internal and external ones, which will be responsible for two different tasks. In our new approach we propose to negate this separation and use only one type of nodes. Using that assumption we manage to significantly shorten the time of segmentation while maintaining its quality.

Abstract

Previous research has shown that repeated interactions can cause iconicity in signals to reduce. However, data from several recent studies has shown the opposite trend: an increase in iconicity as the result of repeated interactions. Here, we discuss whether signals may become less or more iconic as a result of the modality used to produce them. We review several recent experimental results before presenting new data from multi-modal signals, where visual input creates audio feedback. Our results show that the growth in iconicity present in the audio information may come at a cost to iconicity in the visual information. Our results have implications for how we think about and measure iconicity in artificial signalling experiments. Further, we discuss how iconicity in real world speech may stem from auditory, kinetic or visual information, but iconicity in these different modalities may conflict.

Abstract

Young children demonstrate the ability to make inferences about the preferences of other agents based on their choices. However, there exists no overarching account of what children are doing when they learn about preferences or how they use that knowledge. We use a rational model of preference learning, drawing on ideas from economics and computer science, to explain the behavior of children in several recent experiments. Specifically, we show how a simple econometric model can be extended to capture two- to four-year-olds’ use of statistical information in inferring preferences, and their generalization of these preferences.

Abstract

We examined how communicators can switch between speaker and listener role with such accurate timing. During conversations, the majority of role transitions happens with a gap or overlap of only a few hundred milliseconds. This suggests that listeners can predict when the turn of the current speaker is going to end. Our hypothesis is that listeners know when a turn ends because they know how it ends. Anticipating the last words of a turn can help the next speaker in predicting when the turn will end, and also in anticipating the content of the turn, so that an appropriate response can be prepared in advance. We used the stimuli material of an earlier experiment (De Ruiter, Mitterer & Enfield, 2006), in which subjects were listening to turns from natural conversations and had to press a button exactly when the turn they were listening to ended. In the present experiment, we investigated if the subjects can complete those turns when only an initial fragment of the turn is presented to them. We found that the subjects made better predictions about the last words of those turns that had more accurate responses in the earlier button press experiment.

Abstract

Speech rate is known to modulate perception of temporally ambiguous speech sounds. For instance, a vowel may be perceived as short when the immediate speech context is slow, but as long when the context is fast. Yet, effects of long-term tracking of speech rate are largely unexplored. Two experiments tested whether long-term tracking of rate influences perception of the temporal Dutch vowel contrast /ɑ/-/a:/. In Experiment 1, one low-rate group listened to 'neutral' rate speech from talker A and to slow speech from talker B. Another high-rate group was exposed to the same neutral speech from A, but to fast speech from B. Between-group comparison of the 'neutral' trials revealed that the low-rate group reported a higher proportion of /a:/ in A's 'neutral' speech, indicating that A sounded faster when B was slow. Experiment 2 tested whether one's own speech rate also contributes to effects of long-term tracking of rate. Here, talker B's speech was replaced by playback of participants' own fast or slow speech. No evidence was found that one's own voice affected perception of talker A in larger speech contexts. These results carry implications for our understanding of the mechanisms involved in rate-dependent speech perception and of dialogue.

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

Words are reduced in spontaneous speech. If reductions are constrained by functional (i.e., perception and production) constraints, they should not be arbitrary. This hypothesis was tested by examing the pronunciations of high- to mid-frequency words in a Dutch and a German spontaneous speech corpus. In logistic-regression models the "reduction likelihood" of a phoneme was predicted by fixed-effect predictors such as position within the word, word length, word frequency, and stress, as well as random effects such as phoneme identity and word. The models for Dutch and German show many communalities. This is in line with the assumption that similar functional constraints influence reductions in both languages.

Abstract

Learning how words refer to aspects of the environment is a complex task, but one that is supported by numerous cues within the environment which constrain the possibilities for matching words to their intended referents. In this paper we tested the predictions of a computational model of multiple cue integration for word learning, that predicted variation in the presence of cues provides an optimal learning situation. In a cross-situational learning task with adult participants, we varied the reliability of presence of distributional, prosodic, and gestural cues. We found that the best learning occurred when cues were often present, but not always. The effect of variability increased the salience of individual cues for the learner, but resulted in robust learning that was not vulnerable to individual cues’ presence or absence. Thus, variability of multiple cues in the language-learning environment provided the optimal circumstances for word learning.

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

Sign languages stand out in that there is high prevalence of
conventionalised linguistic forms that map directly to their
referent (i.e., iconic). Hearing adults show low performance
when asked to guess the meaning of iconic signs suggesting
that their iconic features are largely inaccessible to them.
However, it has not been investigated whether speakers’
gestures, which also share the property of iconicity, may
assist non-signers in guessing the meaning of signs. Results
from a pantomime generation task (Study 1) show that
speakers’ gestures exhibit a high degree of systematicity, and
share different degrees of form overlap with signs (full,
partial, and no overlap). Study 2 shows that signs with full
and partial overlap are more accurately guessed and are
assigned higher iconicity ratings than signs with no overlap.
Deaf and hearing adults converge in their iconic depictions
for some concepts due to the shared conceptual knowledge
and manual-visual modality.

Abstract

This paper examines the use of iconic words in early conversations between children and caregivers. The longitudinal data include a span of six observations of 35 children-parent dyads in the same semi-structured activity. Our findings show that children’s speech initially has a high proportion of iconic words, and over time, these words become diluted by an increase of arbitrary words. Parents’ speech is also initially high in iconic words, with a decrease in the proportion of iconic words over time – in this case driven by the use of fewer iconic words. The level and development of iconicity are related to individual differences in the children’s cognitive skills. Our findings fit with the hypothesis that iconicity facilitates early word learning and may play an important role in learning to produce new words.

Abstract

Cognitive neuroscience approaches the brain as a cognitive system: a system that functionally is conceptualized in terms of information processing. We outline some aspects of this concept and consider a physical system to be an information processing device when a subclass of its physical states can be viewed as representational/cognitive and transitions between these can be conceptualized as a process operating on these states by implementing operations on the corresponding representational structures. We identify a generic and fundamental problem in cognition: sequentially organized structured processing. Structured sequence processing provides the brain, in an essential sense, with its processing logic. In an approach addressing this problem, we illustrate how to integrate levels of analysis within a framework of adaptive dynamical systems. We note that the dynamical system framework lends itself to a description of asynchronous event-driven devices, which is likely to be important in cognition because the brain appears to be an asynchronous processing system. We use the human language faculty and natural language processing as a concrete example through out.

Abstract

A key challenge for cognitive neuroscience is to decipher the representational schemes of the brain. A recent class of decoding algorithms for fMRI data, stimulus-feature-based encoding models, is becoming increasingly popular for inferring the dimensions of neural representational spaces from stimulus-feature spaces. We argue that such inferences are not always valid, because decoding can occur even if the neural representational space and the stimulus-feature space use different representational schemes. This can happen when there is a systematic mapping between them. In a simulation, we successfully decoded the binary representation of numbers from their decimal features. Since binary and decimal number systems use different representations, we cannot conclude that the binary representation encodes decimal features. The same argument applies to the decoding of neural patterns from stimulus-feature spaces and we urge caution in inferring the nature of the neural code from such methods. We discuss ways to overcome these inferential limitations.

Abstract

A classic discussion about visual imagery is whether it affords reinterpretation, like discovering two interpretations in the duck/rabbit illustration. Recent findings converge on reinterpretation being possible in visual imagery, suggesting functional equivalence with pictorial representations. However, it is unclear whether such reinterpretations are necessarily a visual-pictorial achievement. To assess this, 68 participants were briefly presented 2-d ambiguous figures. One figure was presented visually, the other via manual touch alone. Afterwards participants mentally rotated the memorized figures as to discover a novel interpretation. A portion (20.6%) of the participants detected a novel interpretation in visual imagery, replicating previous research. Strikingly, 23.6% of participants were able to reinterpret figures they had only felt. That reinterpretation truly involved haptic processes was further supported, as some participants performed co-thought gestures on an imagined figure during retrieval. These results are promising for further development of an Enactivist approach to imagination.

Abstract

Dutch listeners' looks to printed words were tracked while they listened to instructions to click with their mouse on one of them. When presented with targets from word pairs where the first two syllables were segmentally identical but differed in stress location, listeners used stress information to recognize the target before segmental information disambiguated the words. Furthermore, the amount of lexical competition was influenced by the presence or absence of word-initial stress.

Abstract

Segmental as well as suprasegmental information is used by Dutch listeners to recognize words. The time-course of the effect of suprasegmental stress information on spoken-word recognition was investigated in a previous study, in which we tracked Dutch listeners' looks to arrays of four printed words as they listened to spoken sentences. Each target was displayed along with a competitor that did not differ segmentally in its first two syllables but differed in stress placement (e.g., 'CENtimeter' and 'sentiMENT'). The listeners' eye-movements showed that stress information is used to recognize the target before distinct segmental information is available. Here, we examine the role of durational information in this effect. Two experiments showed that initial-syllable duration, as a cue to lexical stress, is not interpreted dependent on the speaking rate of the preceding carrier sentence. This still held when other stress cues like pitch and amplitude were removed. Rather, the speaking rate of the preceding carrier affected the speed of word recognition globally, even though the rate of the target itself was not altered. Stress information modulated lexical competition, but did so independently of the rate of the preceding carrier, even if duration was the only stress cue present.

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

The recognition of emotions of disgust, anger and fear have been shown to be significantly impaired in Huntington’s disease (eg,Sprengelmeyer et al, 1997, 2006; Gray et al, 1997; Milders et al, 2003,Montagne et al, 2006; Johnson et al, 2007; De Gelder et al, 2008). The relative impairment of these emotions might have implied a recognition impairment specific to negative emotions. Could the asymmetric recognition deficits be due not to the complexity of the emotion but rather reflect the complexity of the task? In the current study, 15 Huntington’s patients and 16 control subjects were presented with negative and positive non-speech emotional vocalisations that were to be identified as anger, fear, sadness, disgust, achievement, pleasure and amusement in a forced-choice paradigm. This experiment more accurately matched the negative emotions with positive emotions in a homogeneous modality. The resulting dually impaired ability of Huntington’s patients to identify negative and positive non-speech emotional vocalisations correctly provides evidence for an overall emotional recognition deficit in the disease. These results indicate that previous findings of a specificity in emotional recognition deficits might instead be due to the limitations of the visual modality. Previous experiments may have found an effect of emotional specificy due to the presence of a single positive emotion, happiness, in the midst of multiple negative emotions. In contrast with the previous literature, the study presented here points to a global deficit in the recognition of emotional sounds.

Abstract

This paper presents the first application of polynomial modeling as a means for validating phonological pitch accent labels to German data. It is compared to traditional phonetic analysis (measuring minima, maxima, alignment). The traditional method fares better in classification, but results are comparable in statistical accent pair testing. Robustness tests show that pitch correction is necessary in both cases. The approaches are discussed in terms of their practicability, applicability to other domains of research and interpretability of their results.

Abstract

In the context of the source-filter theory of speech, it is well established that intelligibility is heavily reliant on information carried by the filter, that is, spectral cues (e.g., Faulkner et al., 2001; Shannon et al., 1995). However, the extraction of other types of information in the speech signal, such as emotion and identity, is less well understood. In this study we investigated the extent to which emotion recognition in speech depends on filterdependent cues, using a forced-choice emotion identification task at ten levels of noise-vocoding ranging between one and 32 channels. In addition, participants performed a speech intelligibility task with the same stimuli. Our results indicate that compared to speech intelligibility, emotion recognition relies less on spectral information and more on cues typically signaled by source variations, such as voice pitch, voice quality, and intensity. We suggest that, while the reliance on spectral dynamics is likely a unique aspect of human speech, greater phylogenetic continuity across species may be found in the communication of affect in vocalizations.

Abstract

Research using event-related brain potentials (ERPs) has demonstrated an early differential effect in fronto-central regions when processing emotional, as compared to affectively neutral facial stimuli (e.g., Eimer & Holmes, 2002). In this talk, data demonstrating a similar effect in the auditory domain will be presented. ERPs were recorded in a one-back task where participants had to identify immediate repetitions of emotion category, such as a fearful sound followed by another fearful sound. The stimulus set consisted of non-verbal emotional vocalisations communicating positive and negative sounds, as well as neutral baseline conditions. Similarly to the facial domain, fear sounds as compared to acoustically controlled neutral sounds, elicited a frontally distributed positivity with an onset latency of about 150 ms after stimulus onset. These data suggest the existence of a rapid multi-modal frontocentral mechanism discriminating emotional from non-emotional human signals.

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

Listeners outperform ASR systems in every speech recognition task. However, what is not clear is where this human advantage originates. This paper investigates the role of acoustic feature representations. We test four (MFCCs, PLPs, Mel Filterbanks, Rate Maps) acoustic representations, with and without ‘pitch’ information, using the same backend. The results are compared with listener results at the level of articulatory feature classification. While no acoustic feature representation reached the levels of human performance, both MFCCs and Rate maps achieved good scores, with Rate maps nearing human performance on the classification of voicing. Comparing the results on the most difficult articulatory features to classify showed similarities between the humans and the SVMs: e.g., ‘dental’ was by far the least well identified by both groups. Overall, adding pitch information seemed to hamper classification performance.

Abstract

There is now considerable evidence that fine-grained acoustic-phonetic detail in the speech signal helps listeners to segment a speech signal into syllables and words. In this paper, we compare two computational models of word recognition on their ability to capture and use this finephonetic detail during speech recognition. One model, SpeM, is phoneme-based, whereas the other, newly developed Fine- Tracker, is based on articulatory features. Simulations dealt with modelling the ability of listeners to distinguish short words (e.g., ‘ham’) from the longer words in which they are embedded (e.g., ‘hamster’). The simulations with Fine- Tracker showed that it was, like human listeners, able to distinguish between short words from the longer words in which they are embedded. This suggests that it is possible to extract this fine-phonetic detail from the speech signal and use it during word recognition.

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

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

This paper presents the results of a joint effort of a group of multimodality researchers and tool developers to improve the interoperability between several tools used for the annotation of multimodality. We propose a multimodal annotation exchange format, based on the annotation graph formalism, which is supported by import and export routines in the respective tools

Abstract

The INTERSPEECH 2017 Computational Paralinguistics Challenge addresses three different problems for the first time in research competition under well-defined conditions: In the Addressee sub-challenge, it has to be determined whether speech produced by an adult is directed towards another adult or towards a child; in the Cold sub-challenge, speech under cold has to be told apart from ‘healthy’ speech; and in the Snoring subchallenge, four different types of snoring have to be classified. In this paper, we describe these sub-challenges, their conditions, and the baseline feature extraction and classifiers, which include data-learnt feature representations by end-to-end learning with convolutional and recurrent neural networks, and bag-of-audiowords for the first time in the challenge series

Abstract

This paper presents the steps needed to make a corpus of Dutch spontaneous dialogues accessible for automatic phonetic research aimed at increasing our understanding of reduction phenomena and the role of fine phonetic detail. Since the corpus was not created with automatic processing in mind, it needed to be reshaped. The first part of this paper describes the actions needed for this reshaping in some detail. The second part reports the results of a preliminary analysis of the reduction phenomena in the corpus. For this purpose a phonemic transcription of the corpus was created by means of a forced alignment, first with a lexicon of canonical pronunciations and then with multiple pronunciation variants per word. In this study pronunciation variants were generated by applying a large set of phonetic processes that have been implicated in reduction to the canonical pronunciations of the words. This relatively straightforward procedure allows us to produce plausible pronunciation variants and to verify and extend the results of previous reduction studies reported in the literature.

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

Speakers sometimes modify their gestures during the process of production into adaptors such as hair touching or eye scratching. Such disguised adaptors are evidence that the speaker can monitor their gestures. In this study, we investigated when and how disguised adaptors are first produced by children. Sixty elementary school children participated in this study (ten children in each age group; from 7 to 12 years old). They were instructed to watch a cartoon and retell it to their parents. The results showed that children did not produce disguised adaptors until the age of 8. The disguised adaptors accompany fluent speech until the children are 10 years old and accompany dysfluent speech until they reach 11 or 12 years of age. These results suggest that children start to monitor their gestures when they are 9 or 10 years old. Cognitive changes were considered as factors to influence emergence of disguised adaptors

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

The Data Category Registry is one of the ISO initiatives towards the establishment of standards for Language Resource management, creation and coding. Successful application of the DCR depends on the availability of tools that can interact with it. This paper describes the first steps that have been taken to provide users of the multimedia annotation tool ELAN, with the means to create references from tiers and annotations to data categories defined in the ISO Data Category Registry. It first gives a brief description of the capabilities of ELAN and the structure of the documents it creates. After a concise overview of the goals and current state of the ISO DCR infrastructure, a description is given of how the preliminary connectivity with the DCR is implemented in ELAN

Abstract

Turn-taking in conversation is a cognitively demanding process that proceeds rapidly due to interlocutors utilizing a range of cues
to aid prediction. In the present study we set out to test recent claims that content question words (also called wh-words) sound similar within languages as an adaptation to help listeners predict
that a question is about to be asked. We test whether upcoming questions can be predicted based on the first phoneme of a turn and the prior context. We analyze the Switchboard corpus of English
by means of a decision tree to test whether /w/ and /h/ are good statistical cues of upcoming questions in conversation. Based on the results, we perform a controlled experiment to test whether
people really use these cues to recognize questions. In both studies
we show that both the initial phoneme and the sequential context help predict questions. This contributes converging evidence that elements of languages adapt to pragmatic pressures applied during
conversation.

Abstract

One of the defining features of the Southern Vanuatu language family is the echo-subject (ES) marker (Lynch 2001: 177-178). Canonically, an ES marker indicates that the subject of the clause is coreferential with the subject of the preceding clause. This paper begins with a survey of the various ES systems found in Southern Vanuatu. Two prominent differences amongst the ES systems are: a) the level of obligatoriness of the ES marker; and b) the level of grammatical integration between an ES clauses and the preceding clause. The variation found amongst the ES systems reveals a clear path of grammaticalisation from the VP coordinator *ma in Proto–Southern Vanuatu to the various types of ES marker in contemporary Southern Vanuatu languages

Abstract

One of the most pressing issues in dis-
continuous constituency transition-based
parsing is that the relevant information for
parsing decisions could be located in any
part of the stack or the buffer. In this pa-
per, we propose a solution to this prob-
lem by replacing the structured percep-
tron model with a recursive neural model
that computes a global representation of
the configuration, therefore allowing even
the most remote parts of the configura-
tion to influence the parsing decisions. We
also provide a detailed analysis of how
this representation should be built out of
sub-representations of its core elements
(words, trees and stack). Additionally, we
investigate how different types of swap or-
acles influence the results. Our model is
the first neural discontinuous constituency
parser, and it outperforms all the previ-
ously published models on three out of
four datasets while on the fourth it obtains
second place by a tiny difference.

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

A common Dutch writing error is to confuse a word ending in -d with a neighbor word ending in -dt. In this paper we describe the development of a machine-learning-based disambiguator that can determine which word ending is appropriate, on the basis of its local context. We develop alternative disambiguators, varying between a single monolithic classifier and having multiple confusable experts disambiguate between confusable pairs. Disambiguation accuracy of the best developed disambiguators exceeds 99%; when we apply these disambiguators to an external test set of collected errors, our detection strategy correctly identifies up to 79% of the errors.

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

Motivated form-meaning mappings are pervasive in sign languages, and iconicity has recently been shown to facilitate sign learning from early on. This study investigated the role of iconicity for language acquisition in Turkish Sign Language (TID). Participants were 43 signing children (aged 10 to 45 months) of deaf parents. Sign production ability was recorded using the adapted version of MacArthur Bates Communicative Developmental Inventory (CDI) consisting of 500 items for TID. Iconicity and familiarity ratings for a subset of 104 signs were available. Our results revealed that the iconicity of a sign was positively correlated with the percentage of children producing a sign and that iconicity significantly predicted the percentage of children producing a sign, independent of familiarity or phonological complexity. Our results are consistent with previous findings on sign language acquisition and provide further support for the facilitating effect of iconic form-meaning mappings in sign learning.

Abstract

This paper investigates the processes in comprehending spoken noun-noun compounds, using data from the BALDEY database. BALDEY contains lexicality judgments and reaction times (RTs) for Dutch stimuli for which also linguistic information is included. Two different approaches are combined. The first is based on regression by Dynamic Survival Analysis, which models decisions and RTs as a consequence of the fact that a cumulative density function exceeds some threshold. The parameters of that function are estimated from the observed RT data. The second approach is based on DIANA, a process-oriented computational model of human word comprehension, which simulates the comprehension process with the acoustic stimulus as input. DIANA gives the identity and the number of the word candidates that are activated at each 10 ms time step.

Both approaches show how the processes involved in comprehending compounds change during a stimulus. Survival Analysis shows that the impact of word duration varies during the course of a stimulus. The density of word and non-word hypotheses in DIANA shows a corresponding pattern with different regimes. We show how the approaches complement each other, and discuss additional ways in which data and process models can be combined.

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

About two years ago, the Max Planck Institute for Psycholinguistics in Nijmegen, The Netherlands, started an initiative to install regional language archives in various places around the world, particularly in places where a large number of endangered languages exist and are being documented. These digital archives make use of the LAT archiving framework [1] that the MPI has developed
over the past nine years. This framework consists of a number of web-based tools for depositing, organizing and utilizing linguistic resources in a digital archive. The regional archives are in principle autonomous archives, but they can decide to share metadata descriptions and language resources with the MPI archive in Nijmegen and become part of a grid of linked LAT archives. By doing so, they will also take advantage of the long-term preservation strategy of the MPI archive. This paper describes the reasoning
behind this initiative and how in practice such an archive is set up.

Abstract

Even advanced Spanish speakers of second language English tend to confuse the pronouns ‘he’ and ‘she’, often without even noticing their mistake (Lahoz, 1991). A study by AntónMéndez (2010) has indicated that a possible reason for this error is the fact that Spanish is a pro-drop language. In order to test this hypothesis, we used an extension of Dual-path (Chang, 2002), a computational cognitive model of sentence production, to simulate two models of bilingual speech production of second language English. One model had Spanish (ES) as a native language, whereas the other learned a Spanish-like language that used the pronoun at all times (non-pro-drop Spanish, NPD_ES). When tested on L2 English sentences, the bilingual pro-drop Spanish model produced significantly more gender pronoun errors, confirming that pronoun dropping could indeed be responsible for the gender confusion in natural language use as well.

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

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

This corpus study investigates how children figure out that functional modals
like must can express various flavors of modality. We examine how modality is
expressed in speech to and by children, and find that the way speakers use
modals may obscure their polysemy. Yet, children eventually figure it out. Our
results suggest that some do before age 3. We show that while root and
epistemic flavors are not equally well-represented in the input, there are robust
correlations between flavor and aspect, which learners could exploit to discover
modal polysemy.

Abstract

A not uncommon assumption in psycholinguistics is that the N400 directly indexes high-level semantic integration, the compositional, word-driven construction of sentence- and discourse-level meaning in some language-relevant unification space. The various discourse- and speaker-dependent modulations of the N400 uncovered by us and others are often taken to support this 'compositional integration' position. In my talk, I will argue that these N400 modulations are probably better interpreted as only indirectly reflecting compositional sense-making. The account that I will advance for these N400 effects is a variant of the classic Kutas and Federmeier (2002, TICS) memory retrieval account in which context effects on the word-elicited N400 are taken to reflect contextual priming of LTM access. It differs from the latter in making more explicit that the contextual cues that prime access to a word's meaning in LTM can range from very simple (e.g., a single concept) to very complex ones (e.g., a structured representation of the current discourse). Furthermore, it incorporates the possibility, suggested by recent N400 findings, that semantic retrieval can also be intensified in response to certain ‘relevance signals’, such as strong value-relevance, or a marked delivery (linguistic focus, uncommon choice of words, etc). In all, the perspective I'll draw is that in the context of discourse-level language processing, N400 effects reflect an 'overlay of technologies', with the construction of discourse-level representations riding on top of more ancient sense-making technology.

Abstract

This paper reports two experiments with vowels and consonants as phoneme detection targets in real words. In the first experiment, two relatively distinct vowels were compared with two confusible stop consonants. Response times to the vowels were longer than to the consonants. Response times correlated negatively with target phoneme length. In the second, two relatively distinct vowels were compared with their corresponding semivowels. This time, the vowels were detected faster than the semivowels. We conclude that response time differences between vowels and stop consonants in this task may reflect differences between phoneme categories in the variability of tokens, both in the acoustic realisation of targets and in the' representation of targets by subjects.

Abstract

The emerging area of Geographic Information Systems (GIS) has proven to add an interesting dimension to many research projects. Within the language-sites initiative we have brought together a broad range of links to digital language corpora and resources. Via Google Earth's visually appealing 3D-interface users can spin the globe, zoom into an area they are interested in and access directly the relevant language resources. This paper focuses on several ways of relating the map and the online data (lexica, annotations, multimedia recordings, etc.). Furthermore, we discuss some of the implementation choices that have been made, including future challenges. In addition, we show how scholars (both linguists and anthropologists) are using GIS tools to fulfill their specific research needs by making use of practical examples. This illustrates how both scientists and the general public can benefit from geography-based access to digital language data

Abstract

Listeners require context to understand the casual pronunciation variants of words that are typical of spontaneous speech (Ernestus et al., 2002). The present study reports two auditory lexical decision experiments, investigating listeners' use of semantic contextual information in the comprehension of unreduced and reduced words. We found a strong semantic priming effect for low frequency unreduced words, whereas there was no such effect for reduced words. Word frequency was facilitatory for all words. These results show that semantic context is relevant especially for the comprehension of unreduced words, which is unexpected given the listener driven explanation of reduction in spontaneous speech.

Abstract

This paper gives an overview of the CLARIN project [1], which aims to create a research infrastructure that makes language resources and technology (LRT) available and readily usable to scholars of all disciplines, in particular the humanities and social sciences (HSS).

Abstract

Experimental sentence comprehension studies have shown that superficially similar German clauses with verb-final word order elicit very different garden-path and ERP effects. We show that a computer implementation of the Unification Space parser (Vosse & Kempen, 2000) in the form of a localist-connectionist network can model the observed differences, at least qualitatively. The model embodies a parallel dynamic parser that, in contrast with existing models, does not distinguish between consecutive first-pass and reanalysis stages, and does not use semantic or thematic roles. It does use structural frequency data and animacy information.

Abstract

Two German eye-tracking experiments tested whether top-down expectations interact with acoustically-driven word-recognition processes. Competitor objects with two synonymous names were paired with target objects whose names shared word onsets with either the dominant or the non-dominant name of the competitor. Non-dominant names of competitor objects were either introduced before the test session or not. Eye-movements were monitored while participants heard instructions to click on target objects. Results demonstrate dominant and non-dominant competitor names were considered for recognition, regardless of top-down expectations, though dominant names were always activated more strongly.

Abstract

Recent studies using phoneme detection tasks have shown that spoken-language processing is neither facilitated nor interfered with by optional assimilation, but is inhibited by violation of obligatory assimilation. Interpretation of these results depends on an assessment of their generality, specifically, whether they also obtain when listeners are processing nonnative language. Two separate experiments are presented in which native listeners of German and native listeners of Dutch had to detect a target fricative in legal monosyllabic Dutch nonwords. All of the nonwords were correct realisations in standard Dutch. For German listeners, however, half of the nonwords contained phoneme strings which violate the German fricative assimilation rule. Whereas the Dutch listeners showed no significant effects, German listeners detected the target fricative faster when the German fricative assimilation was violated than when no violation occurred. The results might suggest that violation of assimilation rules does not have to make processing more difficult per se.

Abstract

Lexical recognition is typically slower in L2 than in L1. Part of the difficulty comes from a not precise enough processing of L2 phonemes. Consequently, L2 listeners fail to eliminate candidate words that L1 listeners can exclude from competing for recognition. For instance, the inability to distinguish /r/ from /l/ in rocket and locker makes for Japanese listeners both words possible candidates when hearing their onset (e.g., Cutler, Weber, and Otake, 2006). The L2 disadvantage can, however, be dispelled: For L2 listeners, but not L1 listeners, L2 speech from a non-native talker with the same language background is known to be as intelligible as L2 speech from a native talker (e.g., Bent and Bradlow, 2003). A reason for this may be that L2 listeners have ample experience with segmental deviations that are characteristic for their own accent. On this account, only phonemic deviations that are typical for the listeners’ own accent will cause spurious lexical activation in L2 listening (e.g., English magic pronounced as megic for Dutch listeners). In this talk, I will present evidence from cross-modal priming studies with a variety of L2 listener groups, showing how the processing of phonemic deviations is accent-specific but withstands fine phonetic differences.

Abstract

Lexical recognition is typically slower in L2 than in L1. Part of the difficulty comes from a not precise enough processing of L2 phonemes. Consequently, L2 listeners fail to eliminate candidate words that L1 listeners can exclude from competing for recognition. For instance, the inability to distinguish /r/ from /l/ in rocket and locker makes for Japanese listeners both words possible candidates when hearing their onset (e.g., Cutler, Weber, and Otake, 2006). The L2 disadvantage can, however, be dispelled: For L2 listeners, but not L1 listeners, L2 speech from a non-native talker with the same language background is known to be as intelligible as L2 speech from a native talker (e.g., Bent and Bradlow, 2003). A reason for this may be that L2 listeners have ample experience with segmental deviations that are characteristic for their own accent. On this account, only phonemic deviations that are typical for the listeners’ own accent will cause spurious lexical activation in L2 listening (e.g., English magic pronounced as megic for Dutch listeners). In this talk, I will present evidence from cross-modal priming studies with a variety of L2 listener groups, showing how the processing of phonemic deviations is accent-specific but withstands fine phonetic differences.

Abstract

Set is widely used as a kind of basic data structure. However, when it is used for large scale data set the cost of storage, search and transport is overhead. The bloom filter uses a fixed size bit string to represent elements in a static set, which can reduce storage space and search cost that is a fixed constant. The time-space efficiency is achieved at the cost of a small probability of false positive in membership query. However, for many applications the space savings and locating time constantly outweigh this drawback. Dynamic bloom filter (DBF) can support concisely representation and approximate membership queries of dynamic set instead of static set. It has been proved that DBF not only possess the advantage of standard bloom filter, but also has better features when dealing with dynamic set. This paper proposes a time-dependent multiple bit-strings bloom filter (TMBF) which roots in the DBF and targets on dynamic incremental set. TMBF uses multiple bit-strings in time order to present a dynamic increasing set and uses backward searching to test whether an element is in a set. Based on the system logs from a real P2P file sharing system, the evaluation shows a 20% reduction in searching cost compared to DBF.

Abstract

We describe ViCoS, a tool for constructing and visualising conceptual spaces in the area of language documentation. ViCoS allows users to enrich existing lexical information about the words of a language with conceptual knowledge. Their work towards language-based, informal ontology building must be supported by easy-to-use workflows and supporting software, which we will demonstrate.