Publications

Abstract

Continuous vector word representations (or
word embeddings) have shown success in cap-turing semantic relations between words, as evidenced by evaluation against behavioral data of adult performance on semantic tasks (Pereira et al., 2016). Adult semantic knowl-edge is the endpoint of a language acquisition process; thus, a relevant question is whether these models can also capture emerging word
representations of young language learners. However, the data for children’s semantic knowledge across development is scarce. In this paper, we propose to bridge this gap by using Age of Acquisition norms to evaluate word embeddings learnt from child-directed input. We present two methods that evaluate word embeddings in terms of (a) the semantic neighbourhood density of learnt words, and (b) con-
vergence to adult word associations. We apply our methods to bag-of-words models, and find that (1) children acquire words with fewer semantic neighbours earlier, and (2) young learners only attend to very local context. These findings provide converging evidence for validity of our methods in understanding the prerequisite features for a distributional model of word learning.

Abstract

Proficient readers typically fixate near the center of a word, with a slight bias towards word onset. We explore a novel account of this phenomenon based on combining information-theory with visual perceptual constraints in a connectionist model of visual word recognition. This account posits that the amount of information-content available for word identification varies across fixation locations and across languages, thereby explaining the overall fixation location bias in different languages, making the novel prediction that certain words are more readily identified when fixating at an atypical fixation location, and predicting specific cross-linguistic differences. We tested these predictions across several simulations in English and Hebrew, and in a pilot behavioral experiment. Results confirmed that the bias to fixate closer to word onset aligns with maximizing information in the visual signal, that some words are more readily identified at atypical fixation locations, and that these effects vary to some degree across languages.

Abstract

Most work on part-of-speech (POS) tagging is focused on high resource languages, or examines low-resource and active learning settings through simulated studies. We evaluate POS tagging techniques on an actual endangered language, Griko. We present a resource that contains 114 narratives in Griko, along with sentence-level translations in Italian, and provides gold annotations for the test set. Based on a previously collected small corpus, we investigate several traditional methods, as well as methods that take advantage of monolingual data or project cross-lingual POS tags. We show that the combination of a semi-supervised method with cross-lingual transfer is more appropriate for this extremely challenging setting, with the best tagger achieving an accuracy of 72.9%. With an applied active learning scheme, which we use to collect sentence-level annotations over the test set, we achieve improvements of more than 21 percentage points

Abstract

A production experiment investigated the tonal shape of Finnish finite verbs in transitive sentences without narrow focus. Traditional descriptions of Finnish stating that non-focused finite verbs do not receive accents were only partly supported. Verbs were found to have a consistently smaller pitch range than words in other word classes, but their pitch contours were neither flat nor explainable by pure interpolation.

Abstract

The term “uptalk” describes utterance-final pitch rises that carry no sentence-structural information. Uptalk is usually dialectal or sociolectal, and Australian English (AusEng) is particularly known for this attribute. We ask here whether experience with an uptalk variety affects listeners’ ability to categorise rising pitch contours on the basis of the timing and height of their onset and offset. Listeners were two groups of English-speakers (AusEng, and American English), and three groups of listeners with L2 English: one group with Mandarin as L1 and experience of listening to AusEng, one with German as L1 and experience of listening to AusEng, and one with German as L1 but no AusEng experience. They heard nouns (e.g. flower, piano) in the framework “Got a NOUN”, each ending with a pitch rise artificially manipulated on three contrasts: low vs. high rise onset, low vs. high rise offset and early vs. late rise onset. Their task was to categorise the tokens as “question” or “statement”, and we analysed the effect of the pitch contrasts on their judgements. Only the native AusEng listeners were able to use the pitch contrasts systematically in making these categorisations.

Abstract

In the paper we describe a new attempt to come to automatic detectors processing real scene audio-video streams that can be used by researchers world-wide to speed up their annotation and analysis work. Typically these recordings are taken in field and experimental situations mostly with bad quality and only little corpora preventing to use standard stochastic pattern recognition techniques. Audio/video processing components are taken out of the expert lab and are integrated in easy-to-use interactive frameworks so that the researcher can easily start them with modified parameters and can check the usefulness of the created annotations. Finally a variety of detectors may have been used yielding a lattice of annotations. A flexible search engine allows finding combinations of patterns opening completely new analysis and theorization possibilities for the researchers who until were required to do all annotations manually and who did not have any help in pre-segmenting lengthy media recordings.

Abstract

Annotation of digital recordings in humanities research still is, to a largeextend, a process that is performed manually. This paper describes the firstpattern recognition based software components developed in the AVATecH projectand their integration in the annotation tool ELAN. AVATecH (AdvancingVideo/Audio Technology in Humanities Research) is a project that involves twoMax Planck Institutes (Max Planck Institute for Psycholinguistics, Nijmegen,Max Planck Institute for Social Anthropology, Halle) and two FraunhoferInstitutes (Fraunhofer-Institut für Intelligente Analyse- undInformationssysteme IAIS, Sankt Augustin, Fraunhofer Heinrich-Hertz-Institute,Berlin) and that aims to develop and implement audio and video technology forsemi-automatic annotation of heterogeneous media collections as they occur inmultimedia based research. The highly diverse nature of the digital recordingsstored in the archives of both Max Planck Institutes, poses a huge challenge tomost of the existing pattern recognition solutions and is a motivation to makesuch technology available to researchers in the humanities.

Abstract

Data augmentation techniques have been widely used in visual recognition tasks as it is easy to generate new
data by simple and straight forward image transformations. However, when it comes to text data augmen-
tations, it is difficult to find appropriate transformation techniques which also preserve the contextual and
grammatical structure of language texts. In this paper, we explore various text data augmentation techniques
in text space and word embedding space. We study the effect of various augmented datasets on the efficiency
of different deep learning models for relation classification in text.

Abstract

Artificial lexicons have previously been used to examine the time course of the learning and recognition of spoken words, the role of segment type in word learning, and the integration of context during spoken word recognition. However, in all of these studies the experimenter determined the frequency and order of the words to be learned. In three experiments, we asked whether adult learners choose to listen to novel words in a particular order based on their acoustic similarity. We use a new paradigm for learning an artificial lexicon in which the learner, rather than the experimenter, determines the order and frequency of exposure to items. We analyze both the proportions of selections and the temporal clustering of subjects' sampling of lexical neighborhoods during training as well as their performance during repeated testing phases (accuracy and reaction time) to determine the time course of learning these neighborhoods. In the first experiment, subjects sampled the high and low density neighborhoods randomly in early learning, and then over-sampled the high density neighborhood until test performance on both neighborhoods reached asymptote. A second experiment involved items similar to the first, but also neighborhoods that are not fully revealed at the start of the experiment. Subjects adjusted their training patterns to focus their selections on neighborhoods of increasing density was revealed; evidence of learning in the test phase was slower to emerge than in the first experiment, impaired by the presence of additional sets of items of varying density. Crucially, in both the first and second experiments there was no effect of dense vs. sparse neighborhood in the accuracy results, which is accounted for by subjects’ over-sampling of items from the dense neighborhood. The third experiment was identical in design to the second except for a second day of further training and testing on the same items. Testing at the beginning of the second day showed impaired, not improved, accuracy, except for the consistently dense items. Further training, however, improved accuracy for some items to above Day 1 levels. Overall, these results provide a new window on the time-course of learning an artificial lexicon and the role that learners’ implicit preferences, stemming from their self-selected experience with the entire lexicon, play in learning highly confusable words.

Abstract

The event-related potential (ERP) component named phonological mismatch negativity (PMN) arises when listeners hear an unexpected word form in a spoken sentence [1]. The PMN is thought to reflect the mismatch between expected and perceived auditory speech input. In this paper, we use the PMN to test a central premise in the predictive coding framework [2], namely that the mismatch between prior expectations and sensory input is an important mechanism of perception. We test this with natural speech materials containing approximately 50,000 word tokens. The corresponding EEG-signal was recorded while participants (n = 48) listened to these materials. Following [3], we quantify the mismatch with two word probability distributions (WPD): a WPD based on preceding context, and a WPD that is additionally updated based on the incoming audio of the current word. We use the between-WPD cross entropy for each word in the utterances and show that a higher cross entropy correlates with a more negative PMN. Our results show that listeners anticipate auditory input while processing each word in naturalistic speech. Moreover, complementing previous research, we show that predictive language processing occurs across the whole probability spectrum.

Abstract

The mismatch between top-down predicted and bottom-up perceptual input is an important mechanism of perception according to the predictive coding framework (Friston, [1]). In this paper we develop and validate a new information-theoretic measure that quantifies the mismatch between expected and observed auditory input during speech processing. We argue that such a mismatch measure is useful for the study of speech processing. To compute the mismatch measure, we use naturalistic speech materials containing approximately 50,000 word tokens. For each word token we first estimate the prior word probability distribution with the aid of statistical language modelling, and next use automatic speech recognition to update this word probability distribution based on the unfolding speech signal. We validate the mismatch measure with multiple analyses, and show that the auditory-based update improves the probability of the correct word and lowers the uncertainty of the word probability distribution. Based on these results, we argue that it is possible to explicitly estimate the mismatch between predicted and perceived speech input with the cross entropy between word expectations computed before and after an auditory update.

Abstract

1. Introduction External input is necessary to acquire language. Consequently, the comprehension of various constituents of language, such as lexical items or syntactic and semantic structures should emerge at the same time as or even precede their production. However, in the case of pronouns this general assumption does not seem to hold. On the contrary, while children at the age of four use pronouns and reflexives appropriately during production (de Villiers, et al. 2006), a number of comprehension studies across different languages found chance performance in pronoun trials up to the age of seven, which co-occurs with a high level of accuracy in reflexive trials (for an overview see e.g. Conroy, et al. 2009; Elbourne 2005).

Abstract

In the present paper we show that a general-purpose word learning model can simulate several important findings from recent experiments in language acquisition. Both the addition of background noise and varying the speaker have been found to influence infants’ performance during word recognition experiments. We were able to replicate this behaviour in our artificial word learning agent. We use the results to discuss both advantages and limitations of computational models of language acquisition.

Abstract

The current study investigates whether mentalizing, or taking the perspective of your interlocutor, plays an essential role throughout a conversation or whether it is mostly used in reaction to misunderstandings. This study is the first to use a brain-imaging method, MEG, to answer this question. In a first phase of the experiment, MEG participants interacted "live" with a confederate who set naming precedents for certain pictures. In a later phase, these precedents were sometimes broken by a speaker who named the same picture in a different way. This could be done by the same speaker, who set the precedent, or by a different speaker. Source analysis of MEG data showed that in the 800 ms before the naming, when the picture was already on the screen, episodic memory and language areas were activated, but no mentalizing areas, suggesting that the speaker's naming intentions were not anticipated by the listener on the basis of shared experiences. Mentalizing areas only became activated after the same speaker had broken a precedent, which we interpret as a reaction to the violation of conversational pragmatics.

Abstract

Rapid Automatized Naming (RAN) is a powerful tool for pre- dicting future reading skill. A person’s ability to quickly name symbols as they scan a table is related to higher-level reading proficiency in adults and is predictive of future literacy gains in children. However, noticeable differences are present in the strategies or patterns within groups having similar task comple- tion times. Thus, a further stratification of RAN dynamics may lead to better characterization and later intervention to support reading skill acquisition. In this work, we analyze the dynamics of the eyes, voice, and the coordination between the two during performance. It is shown that fast performers are more similar to each other than to slow performers in their patterns, but not vice versa. Further insights are provided about the patterns of more proficient subjects. For instance, fast performers tended to exhibit smoother behavior contours, suggesting a more sta- ble perception-production process.

Abstract

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

Abstract

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

Learning a language involves learning how to map specific forms onto their associated meanings. Such mappings can utilise arbitrariness and non-arbitrariness, yet, our understanding of how these two systems operate at different stages of vocabulary development is still not fully understood. The Sound-Symbolism Bootstrapping Hypothesis (SSBH) proposes that sound-symbolism is essential for word learning to commence, but empirical evidence of exactly how sound-symbolism influences language learning is still sparse. It may be the case that sound-symbolism supports acquisition of categories of meaning, or that it enables acquisition of individualized word meanings. In two Experiments where participants learned form-meaning mappings from either sound-symbolic or arbitrary languages, we demonstrate the changing roles of sound-symbolism and arbitrariness for different vocabulary sizes, showing that sound-symbolism provides an advantage for learning of broad categories, which may then transfer to support learning individual words, whereas an arbitrary language impedes acquisition of categories of sound to meaning.

Abstract

We describe our computer-supported framework to overcome the rule of metadata schism. It combines the use of controlled vocabularies, managed by a data category registry, with a component-based approach, where the categories can be combined to yield complex metadata structures. A metadata scheme devised in this way will thus be grounded in its use of categories. Schema designers will profit from existing prefabricated larger building blocks, motivating re-use at a larger scale. The common base of any two metadata schemes within this framework will solve, at least to a good extent, the semantic interoperability problem, and consequently, further promote systematic use of metadata for existing resources and tools to be shared.

Abstract

Unlike most of the world's languages, Korean distinguishes three types of voiceless stops, namely lenis, fortis, and aspirated stops. All occur at three places of articulation. In previous work, acoustic measurements are mostly collapsed over the three places of articulation. This study therefore provides acoustic measurements of Korean lenis, fortis, and aspirated stops at all three places of articulation separately. Clear differences are found among the acoustic characteristics of the stops at the different places of articulation

Abstract

We investigated the extent to which emotionally valenced words automatically cue spatio-motor representations. Participants made speeded button presses, moving their hand upward or downward while viewing words with positive or negative valence. Only the color of the words was relevant to the response; on target trials, there was no requirement to read the words or process their meaning. In Experiment 1, upward responses were faster for positive words, and downward for negative words. This effect was extinguished, however, when words were repeated. In Experiment 2, participants performed the same primary task with the addition of distractor trials. Distractors either oriented attention toward the words’ meaning or toward their color. Congruity effects were increased with orientation to meaning, but eliminated with orientation to color. When people read words with emotional valence, vertical spatio-motor representations are activated highly automatically, but this automaticity is modulated by repetition and by attentional orientation to the words’ form or meaning.

Abstract

This paper investigates whether surprisal theory can account for differential processing difficulty in the NP-/S-coordination ambiguity in Dutch. Surprisal is estimated using a Probabilistic Context-Free Grammar (PCFG), which is induced from an automatically annotated corpus. We find that our lexicalized surprisal model can account for the reading time data from a classic experiment on this ambiguity by Frazier (1987). We argue that syntactic and lexical probabilities, as specified in a PCFG, are sufficient to account for what is commonly referred to as an NP-coordination preference.

Abstract

Speech input causes listeners to activate multiple
candidate words which then compete with one
another. These include onset competitors, that share a
beginning (bumper, butter), but also, counterintuitively,
rhyme competitors, sharing an ending
(bumper, jumper). In L1, competition is typically
stronger for onset than for rhyme. In L2, onset
competition has been attested but rhyme competition
has heretofore remained largely unexamined. We
assessed L1 (Dutch) and L2 (English) word
recognition by the same late-bilingual individuals. In
each language, eye gaze was recorded as listeners
heard sentences and viewed sets of drawings: three
unrelated, one depicting an onset or rhyme competitor
of a word in the input. Activation patterns revealed
substantial onset competition but no significant
rhyme competition in either L1 or L2. Rhyme
competition may thus be a “luxury” feature of
maximally efficient listening, to be abandoned when
resources are scarcer, as in listening by late
bilinguals, in either language.

Abstract

Across cultures, people conceptualize time as if it flows along a horizontal timeline, but the direction of this implicit timeline is culture-specific: in cultures with left-to-right orthography (e.g., English-speaking cultures) time appears to flow rightward, but in cultures with right-to-left orthography (e.g., Arabic-speaking cultures) time flows leftward. Can orthography influence implicit time representations independent of other cultural and linguistic factors? Native Dutch speakers performed a space-time congruity task with the instructions and stimuli written in either standard Dutch or mirror-reversed Dutch. Participants in the Standard Dutch condition were fastest to judge past-oriented phrases by pressing the left button and future-oriented phrases by pressing the right button. Participants in the Mirror-Reversed Dutch condition showed the opposite pattern of reaction times, consistent with results found previously in native Arabic and Hebrew speakers. These results demonstrate a causal role for writing direction in shaping implicit mental representations of time.

Abstract

We investigate children’s online predictive processing as it occurs naturally, in conversation. We showed 1–7 year-olds short videos of improvised conversation between puppets, controlling for available linguistic information through phonetic manipulation. Even one- and two-year-old children made accurate and spontaneous predictions about when a turn-switch would occur: they gazed at the upcoming speaker before they heard a response begin. This predictive skill relies on both lexical and prosodic information together, and is not tied to either type of information alone. We suggest that children integrate prosodic, lexical, and visual information to effectively predict upcoming linguistic material in conversation.

Abstract

Previous studies on focus marking in French have shown that post-focus deaccentuation, phrasing and phonetic cues like peak height and duration are employed to encode narrow focus but tonal patterns appear to be irrelevant. These studies either examined Standard French or did not control for the regional varieties spoken by the speakers. The present study investigated the use of all these cues in expressing narrow focus in naturally spoken declarative sentences in Toulousian French. It was found that similar to Standard French, Toulousian French uses post-focus deaccentuation and phrasing to mark focus. Different from Standard French, Toulousian French does not use the phonetic cues but use tonal patterns to encode focus. Tonal patterns ending with H\% occur more frequently in the VPs when the subject is in focus but tonal patterns ending with L\% occur more frequently in the VPs when the object is in focus. Our study thus provides a first insight into the similarities and differences in focus marking between Toulousian French and Standard French.

Abstract

Speaker diarization (answering 'who spoke when') is a widely researched subject within speech technology. Numerous experiments have been run on datasets built from broadcast news, meeting data, and call centers—the task sometimes appears close to being solved. Much less work has begun to tackle the hardest diarization task of all: spontaneous conversations in real-world settings. Such diarization would be particularly useful for studies of language acquisition, where researchers investigate the speech children produce and hear in their daily lives. In this paper, we study audio gathered with a recorder worn by small children as they went about their normal days. As a result, each child was exposed to different acoustic environments with a multitude of background noises and a varying number of adults and peers. The inconsistency of speech and noise within and across samples poses a challenging task for speaker diarization systems, which we tackled via retraining and data augmentation techniques. We further studied sources of structured variation across raw audio files, including the impact of speaker type distribution, proportion of speech from children, and child age on diarization performance. We discuss the extent to which these findings might generalize to other samples of speech in the wild.

Abstract

Part of the remarkable efficiency of listening is
accommodation to unfamiliar talkers’ specific
pronunciations by retuning of phonemic intercategory
boundaries. Such retuning occurs in second
(L2) as well as first language (L1); however, recent
research with emigrés revealed successful adaptation
in the environmental L2 but, unprecedentedly, not in
L1 despite continuing L1 use. A possible explanation
involving relative exposure to novel talkers is here
tested in heritage language users with Mandarin as
family L1 and English as environmental language. In
English, exposure to an ambiguous sound in
disambiguating word contexts prompted the expected
adjustment of phonemic boundaries in subsequent
categorisation. However, no adjustment occurred in
Mandarin, again despite regular use. Participants
reported highly asymmetric interlocutor counts in the
two languages. We conclude that successful retuning
ability requires regular exposure to novel talkers in
the language in question, a criterion not met for the
emigrés’ or for these heritage users’ L1.

Abstract

In two experiments, Mandarin listeners resolved potential syntactic ambiguities in spoken utterances in (a) their native language (L1) and (b) English which they had learned as a second language (L2). A new disambiguation task was used, requiring speeded responses to select the correct meaning for structurally ambiguous sentences. Importantly, the ambiguities used in the study are identical in Mandarin and in English, and production data show that prosodic disambiguation of this type of ambiguity is also realised very similarly in the two languages. The perceptual results here showed however that listeners’ response patterns differed for L1 and L2, although there was a significant increase in similarity between the two response patterns with increasing exposure to the L2. Thus identical ambiguity and comparable disambiguation patterns in L1 and L2 do not lead to immediate application of the appropriate L1 listening strategy to L2; instead, it appears that such a strategy may have to be learned anew for the L2.

Abstract

Using a phoneme detection task, the present series of
experiments examines whether listeners can entrain to
different combinations of prosodic cues to predict where focus
will fall in an utterance. The stimuli were recorded by four
female native speakers of Australian English who happened to
have used different prosodic cues to produce sentences with
prosodic focus: a combination of duration cues, mean and
maximum F0, F0 range, and longer pre-target interval before
the focused word onset, only mean F0 cues, only pre-target
interval, and only duration cues. Results revealed that listeners
can entrain in almost every condition except for where
duration was the only reliable cue. Our findings suggest that
listeners are flexible in the cues they use for focus processing.

Abstract

Listeners adapt rapidly to previously unheard talkers by
adjusting phoneme categories using lexical knowledge, in a
process termed lexically-guided perceptual learning. Although
this is firmly established for listening in the native language
(L1), perceptual flexibility in second languages (L2) is as yet
less well understood. We report two experiments examining L1
and L2 perceptual learning, the first in Mandarin-English late
bilinguals, the second in Australian learners of Mandarin. Both
studies showed stronger learning in L1; in L2, however,
learning appeared for the English-L1 group but not for the
Mandarin-L1 group. Phonological mapping differences from
the L1 to the L2 are suggested as the reason for this result.

Abstract

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

Abstract

Recognising continuous speech in a second language is often unexpectedly difficult, as the operation of segmenting speech is so attuned to native-language structure. We report the initial steps in development of a novel training method for second-language listening, focusing on speech segmentation and employing a task designed for studying this: word-spotting. Listeners detect real words in sequences consisting of a word plus a minimal context. The present validation study shows that learners from varying non-English backgrounds successfully perform a version of this task in English, and display appropriate sensitivity to structural factors that also affect segmentation by native English listeners.

Abstract

Vocabularies contain hundreds of thousands of words built from only a handful of phonemes, so that inevitably longer words tend to contain shorter ones. In many languages (but not all) such embedded words occur more often word-initially than word-finally, and this asymmetry, if present, has farreaching consequences for spoken-word recognition. Prior research had ascribed the asymmetry to suffixing or to effects of stress (in particular, final syllables containing the vowel schwa). Analyses of the standard French vocabulary here reveal an effect of suffixing, as predicted by this account, and further analyses of an artificial variety of French reveal that extensive final schwa has an independent and additive effect in promoting the embedding asymmetry.

Abstract

Do interlocutors adjust their conversational strategies to the specific contextual demands of a given situation? Prior studies have yielded conflicting results, making it unclear how strategies vary with demands. We combine insights from qualitative and quantitative approaches in a within-participant experimental design involving two different contexts: spontaneously occurring conversations (SOC) and task-oriented conversations (TOC). We systematically assess backchanneling, other-repair and linguistic alignment. We find that SOC exhibit a higher number of backchannels, a reduced and more generic repair format and higher rates of lexical and syntactic alignment. TOC are characterized by a high number of specific repairs and a lower rate of lexical and syntactic alignment. However, when alignment occurs, more linguistic forms are aligned. The findings show that conversational strategies adapt to specific contextual demands.

Abstract

Speakers often use spatial metaphors to talk about musical pitch (e.g., a low note, a high soprano). Previous experiments suggest that English speakers also think about pitches as high or low in space, even when theyʼre not using language or musical notation (Casasanto, 2010). Do metaphors in language merely reflect pre-existing associations between space and pitch, or might language also shape these non-linguistic metaphorical mappings? To investigate the role of language in pitch tepresentation, we conducted a pair of non-linguistic spacepitch interference experiments in speakers of two languages that use different spatial metaphors. Dutch speakers usually describe pitches as ʻhighʼ (hoog) and ʻlowʼ (laag). Farsi speakers, however, often describe high-frequency pitches as ʻthinʼ (naazok) and low-frequency pitches as ʻthickʼ (koloft). Do Dutch and Farsi speakers mentally represent pitch differently? To find out, we asked participants to reproduce musical pitches that they heard in the presence of irrelevant spatial information (i.e., lines that varied either in height or in thickness). For the Height Interference experiment, horizontal lines bisected a vertical reference line at one of nine different locations. For the Thickness Interference experiment, a vertical line appeared in the middle of the screen in one of nine thicknesses. In each experiment, the nine different lines were crossed with nine different pitches ranging from C4 to G#4 in semitone increments, to produce 81 distinct trials. If Dutch and Farsi speakers mentally represent pitch the way they talk about it, using different kinds of spatial representations, they should show contrasting patterns of cross-dimensional interference: Dutch speakersʼ pitch estimates should be more strongly affected by irrelevant height information, and Farsi speakersʼ by irrelevant thickness information. As predicted, Dutch speakersʼ pitch estimates were significantly modulated by spatial height but not by thickness. Conversely, Farsi speakersʼ pitch estimates were modulated by spatial thickness but not by height (2x2 ANOVA on normalized slopes of the effect of space on pitch: F(1,71)=17,15 p<.001). To determine whether language plays a causal role in shaping pitch representations, we conducted a training experiment. Native Dutch speakers learned to use Farsi-like metaphors, describing pitch relationships in terms of thickness (e.g., a cello sounds ʻthickerʼ than a flute). After training, Dutch speakers showed a significant effect of Thickness interference in the non-linguistic pitch reproduction task, similar to native Farsi speakers: on average, pitches accompanied by thicker lines were reproduced as lower in pitch (effect of thickness on pitch: r=-.22, p=.002). By conducting psychophysical tasks, we tested the ʻWhorfianʼ question without using words. Yet, results also inform theories of metaphorical language processing. According to psycholinguistic theories (e.g., Bowdle & Gentner, 2005), highly conventional metaphors are processed without any active mapping from the source to the target domain (e.g., from space to pitch). Our data, however, suggest that when people use verbal metaphors they activate a corresponding non-linguistic mapping from either height or thickness to pitch, strengthening this association at the expense of competing associations. As a result, people who use different metaphors in their native languages form correspondingly different representations of musical pitch. Casasanto, D. (2010). Space for Thinking. In Language, Cognition and Space: State of the art and new directions. V. Evans & P. Chilton (Eds.), 453-478, London: Equinox Publishing. Bowdle, B. & Gentner, D. (2005). The career of metaphor. Psychological Review, 112, 193-216.

Abstract

Spatial congruity effects have often been interpreted as evidence for metaphorical thinking, but an alternative markedness-based account challenges this view. In two experiments, we directly compared metaphor and markedness explanations for spatial congruity effects, using musical pitch as a testbed. English speakers who talk about pitch in terms of spatial height were tested in speeded space-pitch compatibility tasks. To determine whether space-pitch congruency effects could be elicited by any marked spatial continuum, participants were asked to classify high- and low-frequency pitches as 'high' and 'low' or as 'front' and 'back' (both pairs of terms constitute cases of marked continuums). We found congruency effects in high/low conditions but not in front/back conditions, indicating that markedness is not sufficient to account for congruity effects (Experiment 1). A second experiment showed that congruency effects were specific to spatial words that cued a vertical schema (tall/short), and that congruity effects were not an artifact of polysemy (e.g., 'high' referring both to space and pitch). Together, these results suggest that congruency effects reveal metaphorical uses of spatial schemas, not markedness effects.

Abstract

Humans readily generalize, applying prior knowledge to novel situations and stimuli. Advances in machine learning have begun to approximate and even surpass human performance, but these systems struggle to generalize what they have learned to untrained situations. We present a model based on wellestablished neurocomputational principles that demonstrates human-level generalisation. This model is trained to play one video game (Breakout) and performs one-shot generalisation to a new game (Pong) with different characteristics. The model
generalizes because it learns structured representations that are functionally symbolic (viz., a role-filler binding calculus) from unstructured training data. It does so without feedback, and without requiring that structured representations are specified a priori. Specifically, the model uses neural co-activation to discover which characteristics of the input are invariant and to learn relational predicates, and oscillatory regularities in network firing to bind predicates to arguments. To our knowledge,
this is the first demonstration of human-like generalisation in a machine system that does not assume structured representa-
tions to begin with.

Abstract

Biologically inspired spiking networks are an important tool to study the nature of computation and cognition in neural systems. In this work, we investigate the representational capacity of spiking networks engaged in an identity mapping task. We compare two schemes for encoding symbolic input, one in which input is injected as a direct current and one where input is delivered as a spatio-temporal spike pattern. We test the ability of networks to discriminate their input as a function of the number of distinct input symbols. We also compare performance using either membrane potentials or filtered spike trains as state variable. Furthermore, we investigate how the circuit behavior depends on the balance between excitation and inhibition, and the degree of synchrony and regularity in its internal dynamics. Finally, we compare different linear methods of decoding population activity onto desired target labels. Overall, our results suggest that even this simple mapping task is strongly influenced by design choices on input encoding, state-variables, circuit characteristics and decoding methods, and these factors can interact in complex ways. This work highlights the importance of constraining computational network models of behavior by available neurobiological evidence.

Abstract

In recent years, large scale initiatives like CLARIN set out to overcome the notorious heterogeneity of metadata formats in the domain of language resource. The CLARIN Component Metadata Infrastructure established means for flexible resouce descriptions for the domain of language resources. The Data Category Registry ISOcat and the accompanying Relation Registry foster semantic interoperability within the growing heterogeneous collection of metadata records. This paper describes the CMD Infrastructure focusing on the facilities for semantic mapping, and gives also an overview of the current status in the joint component metadata domain.

Abstract

Previous studies have shown that speakers align their speech to each other at multiple linguistic levels. This study investigates whether alignment is mostly the result of priming from the immediately preceding
speech materials, focussing on pitch and articulation rate (AR). Native Dutch speakers completed sentences, first by themselves (pre-test), then in alternation with Confederate 1 (Round 1), with Confederate 2 (Round 2), with Confederate 1 again
(Round 3), and lastly by themselves again (post-test). Results indicate that participants aligned to the confederates and that this alignment lasted during the post-test. The confederates’ directly preceding sentences were not good predictors for the participants’ pitch and AR. Overall, the results indicate that alignment is more of a global effect than a local priming effect.

Abstract

Pre-lexical representations of speech sounds have been to shown to change dynamically through a mechanism of lexically driven learning. [Norris et al. (2003).] Here we investigated whether this type of learning occurs in native British English (BE) listeners for a word-final stop contrast which is commonly de-voiced in Dutch-accented English. Specifically, this study asked whether the change in pre-lexical representation also encodes information about the position of the critical sound within a word. After exposure to a native Dutch speaker's productions of de-voiced stops in word-final position (but not in any other positions), BE listeners showed evidence of perceptual learning in a subsequent cross-modal priming task, where auditory primes with voiceless final stops (e.g., [si:t], “seat”) facilitated recognition of visual targets with voiced final stops (e.g., “seed”). This learning generalized to test pairs where the critical contrast was in word-initial position, e.g., auditory primes such as [taun] (“town”), facilitated recognition of visual targets like “down”. Control listeners, who had not heard any stops by the speaker during exposure, showed no learning effects. The results suggest that under these exposure conditions, word position is not encoded in the pre-lexical adjustment to the accented phoneme contras

Abstract

This paper shows that the dictation task, a well-
known testing instrument in language education, has
untapped potential as a research tool for studying
speech perception. We describe how transcriptions
can be scored on measures of lexical, orthographic,
phonological, and semantic similarity to target
phrases to provide comprehensive information about
accuracy at different processing levels. The former
three measures are automatically extractable,
increasing objectivity, and the middle two are
gradient, providing finer-grained information than
traditionally used. We evaluate the measures in an
English dictation task featuring phonetically reduced
continuous speech. Whereas the lexical and
orthographic measures emphasize listeners’ word
identification difficulties, the phonological measure
demonstrates that listeners can often still recover
phonological features, and the semantic measure
captures their ability to get the gist of the utterances.
Correlational analyses and a discussion of practical
and theoretical considerations show that combining
multiple measures improves the dictation task’s
utility as a research tool.

Abstract

Lexically guided perceptual learning has traditionally been studied with ambiguous consonant sounds to which native listeners are exposed in a purely receptive listening context. To extend previous research, we investigate whether lexically guided learning applies to a vowel shift encountered by non-native listeners in an interactive dialogue. Dutch participants played a two-player game in English in either a control condition, which contained no evidence for a vowel shift, or a lexically constraining condition, in which onscreen lexical information required them to re-interpret their interlocutor’s /ɪ/ pronunciations as representing /ε/. A phonetic categorization pre-test and post-test were used to assess whether the game shifted listeners’ phonemic boundaries such that more of the /ε/-/ɪ/ continuum came to be perceived as /ε/. Both listener groups showed an overall post-test shift toward /ɪ/, suggesting that vowel perception may be sensitive to directional biases related to properties of the speaker’s vowel space. Importantly, listeners in the lexically constraining condition made relatively more post-test /ε/ responses than the control group, thereby exhibiting an effect of lexically guided adaptation. The results thus demonstrate that non-native listeners can adjust their phonemic boundaries on the basis of lexical information to accommodate a vowel shift learned in interactive conversation.

Abstract

The problem of auxiliary fronting in complex polar questions occupies a prominent position within the nature versus nurture controversy in language acquisition. We employ a model of statistical learning which uses sequential and semantic information to produce utterances from a bag of words. This linear learner is capable of generating grammatical questions without exposure to these structures in its training environment. We also demonstrate that the model performs superior to n-gram learners on this task. Implications for nativist theories of language acquisition are discussed.

Abstract

This dissertation is an ethnographic study of race and other forms of social categorization as approached through the discourse of the indigenous Chachi people of northwestern lowland Ecuador and their Afro-descendant neighbors. It combines the ethnographic methods of social anthropology with the methods of descriptive linguistics, letting social questions about racial formation guide linguistic inquiry. It provides new information about the largely unstudied indigenous South American language Cha’palaa, and connects that information about linguistic form to problems of the study of race and ethnicity in Latin America. Individual descriptive chapters address how the Cha’palaa number system is based on collectivity rather than plurality according to an animacy hierarchy that codes only human and human-like social collectivities, how a nominal set of ethnonyms linked to Chachi oral history become the recipients of collective marking as human collectivities, how those collectivities are co-referentially linked to speech participants through the deployment of the pronominal system, and how the multi-modal resource of gesture adds to these rich resources supplied by the spoken language for the expression of social realities like race. The final chapters address Chachi and Afrodescendant discourses in dialogue with each other and examine naturally occurring speech data to show how the linguistic forms described in previous chapters are used in social interaction. The central argument advances a position that takes the socially constructed status of race seriously and considers that for such constructions to exist as more abstract macro-categories they must be constituted by instances of social interaction, where elements of the social order are observable at the micro-level. In this way localized articulations of social categories become vehicles for the broader circulation of discourses structured by a history of racialized social inequality, revealing the extreme depth of racialization in human social conditioning. This dissertation represents a contribution to the field of linguistic anthropology as well as to descriptive linguistics of South American languages and to critical approaches to race and ethnicity in Latin America.

Abstract

Speaking and listening are complex tasks that we perform on a daily basis, almost without conscious effort. Interestingly, speaking almost never occurs without listening: whenever we speak, we at least hear our own speech. The research in this thesis is concerned with how the perception of our own speech influences our speaking behavior. We show that unconsciously, we actively monitor this auditory feedback of our own speech. This way, we can efficiently take action and adapt articulation when an error occurs and auditory feedback does not correspond to our expectation. Processing the auditory feedback of our speech does not, however, automatically affect speech production. It is subject to a number of constraints. For example, we do not just track auditory feedback, but also its consistency. If auditory feedback is more consistent over time, it has a stronger influence on speech production. In addition, we investigated how auditory feedback during speech is processed in the brain, using magnetoencephalography (MEG). The results suggest the involvement of a broad cortical network including both auditory and motor-related regions. This is consistent with the view that the auditory center of the brain is involved in comparing auditory feedback to our expectation of auditory feedback. If this comparison yields a mismatch, motor-related regions of the brain can be recruited to alter the ongoing articulations.

Abstract

Achieving linguistic proficiency requires identifying words from speech, and discovering the constraints that govern the way those words are used. In a recent study of non-adjacent dependency learning, Frost and Monaghan (2016) demonstrated that learners may perform these tasks together, using similar statistical processes - contrary to prior suggestions. However, in their study, non-adjacent dependencies were marked by phonological cues (plosive-continuant-plosive structure), which may have influenced learning. Here, we test the necessity of these cues by comparing learning across three conditions; fixed phonology, which contains these cues, varied phonology, which omits them, and shapes, which uses visual shape sequences to assess the generality of statistical processing for these tasks. Participants segmented the sequences and generalized the structure in both auditory conditions, but learning was best when phonological cues were present. Learning was around chance on both tasks for the visual shapes group, indicating statistical processing may critically differ across domains.

Abstract

We analyze the problem of response suggestion in a closed domain along a real-world scenario of a digital library. We present a text-processing pipeline to generate question-answer pairs from chat transcripts. On this limited amount of training data, we compare retrieval-based, conditioned-generation, and dedicated representation learning approaches for response suggestion. Our results show that retrieval-based methods that strive to find similar, known contexts are preferable over parametric approaches from the conditioned-generation family, when the training data is limited. We, however, identify a specific representation learning approach that is competitive to the retrieval-based approaches despite the training data limitation.

Abstract

Large-scale graph data in real-world applications is often not static but dynamic,
i. e., new nodes and edges appear over time. Current graph convolution approaches
are promising, especially, when all the graph’s nodes and edges are available dur-
ing training. When unseen nodes and edges are inserted after training, it is not
yet evaluated whether up-training or re-training from scratch is preferable. We
construct an experimental setup, in which we insert previously unseen nodes and
edges after training and conduct a limited amount of inference epochs. In this
setup, we compare adapting pretrained graph neural networks against retraining
from scratch. Our results show that pretrained models yield high accuracy scores
on the unseen nodes and that pretraining is preferable over retraining from scratch.
Our experiments represent a first step to evaluate and develop truly online variants
of graph neural networks.

Abstract

We present multi-modal adversarial autoencoders for recommendation and evaluate them on two different tasks: citation recommendation and subject label recommendation. We analyze the effects of adversarial regularization, sparsity, and different input modalities. By conducting 408 experiments, we show that adversarial regularization consistently improves the performance of autoencoders for recommendation. We demonstrate, however, that the two tasks differ in the semantics of item co-occurrence in the sense that item co-occurrence resembles relatedness in case of citations, yet implies diversity in case of subject labels. Our results reveal that supplying the partial item set as input is only helpful, when item co-occurrence resembles relatedness. When facing a new recommendation task it is therefore crucial to consider the semantics of item co-occurrence for the choice of an appropriate model.

Abstract

We propose a Random-Forest based sign language identification system. The system uses low-level visual features and is based on the hypothesis that sign languages have varying distributions of phonemes (hand-shapes, locations and movements). We evaluated the system on two sign languages -- British SL and Greek SL, both taken from a publicly available corpus, called Dicta Sign Corpus. Achieved average F1 scores are about 95% - indicating that sign languages can be identified with high accuracy using only low-level visual features.

Abstract

We present a vision-based method for signer diarization -- the task of automatically determining "who signed when?" in a video. This task has similar motivations and applications as speaker diarization but has received little attention in the literature. In this paper, we motivate the problem and propose a method for solving it. The method is based on the hypothesis that signers make more movements than their interlocutors. Experiments on four videos (a total of 1.4 hours and each consisting of two signers) show the applicability of the method. The best diarization error rate (DER) obtained is 0.16.

Abstract

This paper presents a Native Language Identification (NLI) system based on TF-IDF weighting schemes and using linear classifiers - support vector machines, logistic regressions and perceptrons. The system was one of the participants of the 2013 NLI Shared Task in the closed-training track, achieving 0.814 overall accuracy for a set of 11 native languages. This accuracy was only 2.2 percentage points lower than the winner's performance. Furthermore, with subsequent evaluations using 10-fold cross-validation (as given by the organizers) on the combined training and development data, the best average accuracy obtained is 0.8455 and the features that contributed to this accuracy are the TF-IDF of the combined unigrams and bigrams of words.

Abstract

We present and solve the speaker diarization problem in a novel way. We hypothesize that the gesturer is the speaker and that identifying the gesturer can be taken as identifying the active speaker. We provide evidence in support of the hypothesis from gesture literature and audio-visual synchrony studies. We also present a vision-only diarization algorithm that relies on gestures (i.e. upper body movements). Experiments carried out on 8.9 hours of a publicly available dataset (the AMI meeting data) show that diarization error rates as low as 15% can be achieved.