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

We present the Retention and Recognition model (R&R), a probabilistic exemplar model that accounts for segmentation in Artificial Language Learning experiments. We show that R&R provides an excellent fit to human responses in three segmentation experiments with adults (Frank et al., 2010), outperforming existing models. Additionally, we analyze the results of the simulations and propose alternative explanations for the experimental findings.

Abstract

Infants learn the meaning of words from accumulated experiences of real-time interactions with their caregivers. To study the effects of visual sensory input on word learning, we recorded infant's view of the world using head-mounted eye trackers during free-flowing play with a caregiver. While playing, infants were exposed to novel label-object mappings and later learning outcomes for these items were tested after the play session. In this study we use a classification based approach to link properties of infants' visual scenes during naturalistic labeling moments to their word learning outcomes. We find that a model which integrates both highly informative and ambiguous sensory evidence is a better fit to infants' individual learning outcomes than models where either type of evidence is taken alone, and that raw labeling frequency is unable to account for the word learning differences we observe. Here we demonstrate how a computational model, using only raw pixels taken from the egocentric scene image, can derive insights on human language learning.

Abstract

This paper briefly presents the current situation of bilingualism in the Philippines,
specifically that of Tagalog-English bilingualism. More importantly, it describes the process of adapting the Multilingual Assessment Instrument for Narratives (LITMUS-MAIN) to Tagalog, the basis of Filipino, which is the country’s national language.
Finally, the results of a pilot study conducted on Tagalog-English bilingual children and
adults (N=27) are presented. The results showed that Story Structure is similar across the
two languages and that it develops significantly with age.

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

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

The use of subject pronouns by bilingual speakers using both a pro-drop and a non-pro-drop language (e.g. Spanish heritage speakers in the USA) is a well-studied topic in research on cross-linguistic influence in language contact situations. Previous studies looking at bilinguals with different proficiency levels have yielded conflicting results on whether there is transfer from the non-pro-drop patterns to the pro-drop language. Additionally, previous research has focused on speech patterns only. In this paper, we study the two modalities of language, speech and gesture, and ask whether and how they reveal cross-linguistic influence on the use of subject pronouns in discourse. We focus on elicited narratives from heritage speakers of Turkish in the Netherlands, in both Turkish (pro-drop) and Dutch (non-pro-drop), as well as from monolingual control groups. The use of pronouns was not very common in monolingual Turkish narratives and was constrained by the pragmatic contexts, unlike in Dutch. Furthermore, Turkish pronouns were more likely to be accompanied by localized gestures than Dutch pronouns, presumably because pronouns in Turkish are pragmatically marked forms. We did not find any cross-linguistic influence in bilingual speech or gesture patterns, in line with studies (speech only) of highly proficient bilinguals. We therefore suggest that speech and gesture parallel each other not only in monolingual but also in bilingual production. Highly proficient heritage speakers who have been exposed to diverse linguistic and gestural patterns of each language from early on maintain monolingual patterns of pragmatic constraints on the use of pronouns multimodally.

Abstract

In many languages modal auxiliaries such as English can, must, may, need, will, ought, want are ambiguous between two types of interpretations: epistemic and root interpretations. In the epistemic interpretation the modal expresses how likely it is that a proposition is true (for example, necessarily, possibly, probably true) while in the root interpretations the modal expresses the obligatoriness, permissibility, desirability, or possibility of a state or event. A central question in much syntactic research on modal auxiliaries has been whether this systematic semantic ambiguity corresponds to a syntactic distinction. A commonly accepted answer has been that in epistemic interpretations the modal verb is a monadic predicate while in root interpretations it is a dyadic predicate, typically a relation between a subject and an infinitival verb. This distinction between monadic and dyadic modal predicates has been modeled syntactically in various ways: (i) in terms of lexical argument structure, that is, as the distinction between raising and control verbs; (ii) in terms of different base positions in the array of functional heads making up the clausal spine, with epistemic modals being higher than root modals; (iii) in terms of a higher syntactic position for epistemically interpreted modals after raising at the level of semantic interpretation (LF raising); (iv) in terms of the nature of the complement of the modal. This chapter evaluates these proposals, drawing on data from, among others, English, Dutch, Icelandic, German, and Catalan and taking into account cross-linguistic differences in the modal systems. One important conclusion is that the alleged correspondence between the epistemic/root distinction and the raising/control distinction is too simple, as there are sentences with root interpretations but a raising syntax. The chapter ends with a list of questions for future research.

Abstract

The Romance languages have a rich numeral system that includes cardinals—providing the bases on which the other types of numeral series are built—ordinals, fractions, collectives, approximatives, distributives, and multiplicatives. Latin plays a decisive and continued role in their formation, both as the language to which many numerals go back directly and as an ongoing source for lexemes and formatives. While the Latin numeral system was synthetic, with a distinct ending for each type of numeral, the Romance numerals often feature more than one (unevenly distributed) marker or structure per series, which feature varying degrees of inherited, borrowed, or innovative elements. Formal consistency is strongest in cardinals, followed by ordinals and then the other types of numeral, which also tend to be more analytic or periphrastic. From a morphological perspective, Romance numerals overall have moved away from the inherited syntheticity, but several series continue to be synthetic formations—at least in part—with morphological markers drawn from Latin that may have undergone functional change (e.g. distributive > ordinal > collective). The underlying syntax of Romance numerals is in line with the overall grammatical patterns of Romance languages, as reflected in the prevalence of word order (with arithmetical correlates), connectors, (partial) loss of agreement, and analyticity. Innovation is prominent in the formation of higher numerals with bases beyond ‘thousand’, of teens and decads in Romanian, and of vigesimals in numerous Romance varieties.

Abstract

Recent work has made available a number of standardized meta- analyses bearing on various aspects of infant language processing. We utilize data from two such meta-analyses (discrimination of vowel contrasts and word segmentation, i.e., recognition of word forms extracted from running speech) to assess whether the published body of empirical evidence supports a bottom-up versus a top-down theory of early phonological development by leveling the power of results from thousands of infants. We predicted that if infants can rely purely on auditory experience to develop their phonological categories, then vowel discrimination and word segmentation should develop in parallel, with the latter being potentially lagged compared to the former. However, if infants crucially rely on word form information to build their phonological categories, then development at the word level must precede the acquisition of native sound categories. Our results do not support the latter prediction. We discuss potential implications and limitations, most saliently that word forms are only one top-down level proposed to affect phonological development, with other proposals suggesting that top-down pressures emerge from lexical (i.e., word-meaning pairs) development. This investigation also highlights general procedures by which standardized meta-analyses may be reused to answer theoretical questions spanning across phenomena.

Abstract

Theories of language acquisition and perceptual learning increasingly rely on statistical learning mechanisms. The current meta-analysis aims to clarify the robustness of this capacity in infancy within the word segmentation literature. Our analysis reveals a significant, small effect size for conceptual replications of Saffran, Aslin, & Newport (1996), and a nonsignificant effect across all studies that incorporate transitional probabilities to segment words. In both conceptual replications and the broader literature, however, statistical learning is moderated by whether stimuli are naturally produced or synthesized. These findings invite deeper questions about the complex factors that influence statistical learning, and the role of statistical learning in language acquisition.

Abstract

Studies have shown that cross-linguistically, consonants at the left edge of higher-level prosodic boundaries tend to be more forcefully articulated than those at lower-level boundaries, a phenomenon known as domain-initial strengthening. This study tests whether similar effects occur in Turkish, using the Autosegmental-Metrical model proposed by Ipek & Jun [1, 2] as the basis for assessing boundary strength. Productions of /t/ and /d/ were elicited in four domain-initial prosodic positions corresponding to progressively higher-level boundaries: syllable, word, intermediate phrase, and Intonational Phrase. A fifth position, nuclear word, was included in order to better situate it within the prosodic hierarchy. Acoustic correlates of articulatory strength were measured, including closure duration for /d/ and /t/, as well as voice onset time and burst energy for /t/. Our results show that closure duration increases cumulatively from syllable to intermediate phrase, while voice onset time and burst energy are not influenced by boundary strength. These findings provide corroborating evidence for Ipek & Jun’s model, particularly for the distinction between word and intermediate phrase boundaries. Additionally, articulatory strength at the left edge of the nuclear word patterned closely with word-initial position, supporting the view that the nuclear word is not associated with a distinct phrasing domain

Abstract

Brain oscillations have been shown to track the slow amplitude fluctuations in speech during comprehension. Moreover, there is evidence that these stimulus-induced cortical rhythms may persist even after the driving stimulus has ceased. However, how exactly this neural entrainment shapes speech perception remains debated. This behavioral study investigated whether and how the frequency and phase of an entrained rhythm would influence the temporal sampling of subsequent speech. In two behavioral experiments, participants were presented with slow and fast isochronous tone sequences, followed by Dutch target words ambiguous between as /ɑs/ “ash” (with a short vowel) and aas /a:s/ “bait” (with a long vowel). Target words were presented at various phases of the entrained rhythm. Both experiments revealed effects of the frequency of the tone sequence on target word perception: fast sequences biased listeners to more long /a:s/ responses. However, no evidence for phase effects could be discerned. These findings show that an entrained rhythm’s frequency, but not phase, influences the temporal sampling of subsequent speech. These outcomes are compatible with theories suggesting that sensory timing is evaluated relative to entrained frequency. Furthermore, they suggest that phase tracking of (syllabic) rhythms by theta oscillations plays a limited role in speech parsing.

Abstract

Speech contains pronounced amplitude modulations in the 1–9 Hz range, correlating with the syllabic rate of speech. Recent models of speech perception propose that this rhythmic nature of speech is central to speech recognition and has beneficial effects on language processing. Here, we investigated the contribution of amplitude modulations to the subjective impression listeners have of public speakers. The speech from US presidential candidates Hillary Clinton and Donald Trump in the three TV debates of 2016 was acoustically analyzed by means of modulation spectra. These indicated that Clinton’s speech had more pronounced amplitude modulations than Trump’s speech, particularly in the 1–9 Hz range. A subsequent perception experiment, with listeners rating the perceived charisma of (low-pass filtered versions of) Clinton’s and Trump’s speech, showed that more pronounced amplitude modulations (i.e., more ‘rhythmic’ speech) increased perceived charisma ratings. These outcomes highlight the important contribution of speech rhythm to charisma perception.

Abstract

Speech is an acoustic signal with inherent amplitude modulations in the 1-9 Hz range. Recent models of speech perception propose that this rhythmic nature of speech is central to speech recognition. Moreover, rhythmic amplitude modulations have been shown to have beneficial effects on language processing and the subjective impression listeners have of the speaker. This study investigated the role of amplitude modulations in the political arena by comparing the speech produced by Hillary Clinton and Donald Trump in the three presidential debates of 2016. Inspection of the modulation spectra, revealing the spectral content of the two speakers’ amplitude envelopes after matching for overall intensity, showed considerably greater power in Clinton’s modulation spectra (compared to Trump’s) across the three debates, particularly in the 1-9 Hz range. The findings suggest that Clinton’s speech had a more pronounced temporal envelope with rhythmic amplitude modulations below 9 Hz, with a preference for modulations around 3 Hz. This may be taken as evidence for a more structured temporal organization of syllables in Clinton’s speech, potentially due to more frequent use of preplanned utterances. Outcomes are interpreted in light of the potential beneficial effects of a rhythmic temporal envelope on intelligibility and speaker perception.

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

This chapter focuses on connectionist modeling in language production, highlighting how
core principles of connectionism provide coverage for empirical observations about
representation and selection at the phonological, lexical, and sentence levels. The first
section focuses on the connectionist principles of localist representations and spreading
activation. It discusses how these two principles have motivated classic models of speech
production and shows how they cover results of the picture-word interference paradigm,
the mixed error effect, and aphasic naming errors. The second section focuses on how
newer connectionist models incorporate the principles of learning and distributed
representations through discussion of syntactic priming, cumulative semantic
interference, sequencing errors, phonological blends, and code-switching

Abstract

This article selectively reviews the literature on politeness across different disciplines—linguistics, anthropology, communications, conversation analysis, social psychology, and sociology—and critically assesses how both theoretical approaches to politeness and research on linguistic politeness phenomena have evolved over the past forty years. Major new developments include a shift from predominantly linguistic approaches to those examining politeness and impoliteness as processes that are embedded and negotiated in interactional and cultural contexts, as well as a greater focus on how both politeness and interactional confrontation and conflict fit into our developing understanding of human cooperation and universal aspects of human social interaction.

Abstract

Acquisition and processing of written and spoken language is an impressive cognitive accomplishment considering the complexity of the tasks. While only humans seem to have evolved to the fullest extent the capacity that underpins these remarkable feats of development and civilization, the exact nature of such capacity has been subject to ongoing research. In this chapter, we focus on language competence and what makes it unique among the communication systems of different species. We then elaborate on the classical debate between nativist and environmentalist accounts of language acquisition, with reference to evidence for and against the critical period hypothesis. After introducing the regularity embedded in different languages and particularly in drastically different orthographies, we present behavioral and neurophysiological evidence for the sensitivity to systematic mapping between orthography and phonology. Because learning to read is to master such mapping, we assume that the ability to use statistical learning to appreciate the dependency among items would contribute to literacy acquisition. Empirical results from behavioral and neuroimaging experiments conducted in our and other laboratories provide support for the close link between statistical learning and literacy acquisition in native and foreign language. Such findings highlight the significance of domain-general statistical learning to domain-specific language acquisition, and point to an important direction for theories and practices of language education.

Abstract

Lexically guided perceptual learni ng refers to the use of lexical knowledge to retune sp eech categories and thereby adapt to a novel talker’s pronunciation. This adaptation has been extensively documented, but primarily for segmental-based learning in English and Dutch. In languages with lexical tone, such as Mandarin Chinese, tonal categories can also be retuned in this way, but segmental category retuning had not been studied. We report two experiment s in which Mandarin Chinese listeners were exposed to an ambiguous mixture of [f] and [s] in lexical contexts favoring an interpretation as either [f] or [s]. Listeners were subsequently more likely to identify sounds along a continuum between [f] and [s], and to interpret minimal word pairs, in a manner consistent with this exposure. Thus lexically guided perceptual learning of segmental categories had indeed taken place, consistent with suggestions that such learning may be a universally available adaptation process

Abstract

Interoperable annotation formats are fundamental to the utility, expansion, and sustainability of collective data repositories.In language development research, shared annotation schemes have been critical to facilitating the transition from raw acoustic data to searchable, structured corpora. Current schemes typically require comprehensive and manual annotation of utterance boundaries and orthographic speech content, with an additional, optional range of tags of interest. These schemes have been enormously successful for datasets on the scale of dozens of recording hours but are untenable for long-format recording corpora, which routinely contain hundreds to thousands of audio hours. Long-format corpora would benefit greatly from (semi-)automated analyses, both on the earliest steps of annotation—voice activity detection, utterance segmentation, and speaker diarization—as well as later steps—e.g., classification-based codes such as child-vs-adult-directed speech, and speech recognition to produce phonetic/orthographic representations. We present an annotation workflow specifically designed for long-format corpora which can be tailored by individual researchers and which interfaces with the current dominant scheme for short-format recordings. The workflow allows semi-automated annotation and analyses at higher linguistic levels. We give one example of how the workflow has been successfully implemented in a large cross-database project.

Abstract

How do children learn to map linguistic forms onto their intended meanings? This chapter begins with an introduction to some theoretical and analytical tools used to study communicative acts. It then turns to communicative act development in spoken and signed language acquisition, including both the early scaffolding and production of communicative acts (both non-verbal and verbal) as well as their later links to linguistic development and Theory of Mind. The chapter wraps up by linking research on communicative act development to the acquisition of conversational skills, cross-linguistic and individual differences in communicative experience during development, and human evolution. Along the way, it also poses a few open questions for future research in this domain.

Abstract

Child-directed speech is argued to facilitate language development, and is found cross-linguistically and cross-culturally to varying degrees. However, previous research has generally focused on short samples of child-caregiver interaction, often in the lab or with experimenters present. We test the generalizability of this phenomenon with an initial descriptive analysis of the speech heard by young children in a large, unique collection of naturalistic, daylong home recordings. Trained annotators coded automatically-detected adult speech 'utterances' from 61 homes across 4 North American cities, gathered from children (age 2-24 months) wearing audio recorders during a typical day. Coders marked the speaker gender (male/female) and intended addressee (child/adult), yielding 10,886 addressee and gender tags from 2,523 minutes of audio (cf. HB-CHAAC Interspeech ComParE challenge; Schuller et al., in press). Automated speaker-diarization (LENA) incorrectly gender-tagged 30% of male adult utterances, compared to manually-coded consensus. Furthermore, we find effects of SES and gender on child-directed and overall speech, increasing child-directed speech with child age, and interactions of speaker gender, child gender, and child age: female caretakers increased their child-directed speech more with age than male caretakers did, but only for male infants. Implications for language acquisition and existing classification algorithms are discussed.

Abstract

In this study, we compared the performance of a long short-term memory (LSTM) neural network to the behavior of human participants on a language task that requires hierarchically structured knowledge. We show that humans interpret ambiguous noun phrases, such as second blue ball, in line with their hierarchical constituent structure. LSTMs, instead, only do
so after unambiguous training, and they do not systematically generalize to novel items. Overall, the results of our simulations indicate that a model can behave hierarchically without relying on hierarchical constituent structure.

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

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

The perceptual processing of speech is a constant interplay of multiple competing albeit convergent processes: acoustic input vs. higher-level representations, universal mechanisms vs. language-specific, veridical traces of speech experience vs. construction and activation of abstract representations. The present summary concerns the third of these issues. The ability to generalise across experience and to deal with resulting abstractions is the hallmark of human cognition, visible even in early infancy. In speech processing, abstract representations play a necessary role in both production and perception. New sorts of evidence are now informing our understanding of the breadth of this role.

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

This paper emphasizes the need for empirical research and objective discovery procedures in semantics, and illustrates a method by which these goals may be obtained. The aim of the methodology described is to provide a description of the internal structure of a semantic field by eliciting the description--in an objective, standardized manner--from a representative group of native speakers. This would produce results that would be equally obtainable by any linguist using the same method under the same conditions with a similarly representative set of informants. The standardized method suggested by the author is the Semantic Differential developed by C. E. Osgood in the 1950's. Applying this method to semantic research, it is further hypothesized that, should different members of a semantic field be employed as concepts on a Semantic Differential task, a factor analysis of the results would reveal the dimensions operative within the body of data. The author demonstrates the use of the Semantic Differential and factor analysis in an actual experiment.

Abstract

In English and Dutch, listeners entrain to prosodic contours to predict where focus will fall in an utterance. However, is this strategy universally available, even in languages with different phonological systems? In a phoneme detection experiment, we examined whether prosodic entrainment is also found in Mandarin Chinese, a tone language, where in principle the use of pitch for lexical identity may take precedence over the use of pitch cues to salience. Consistent with the results from Germanic languages, response times were facilitated when preceding intonation predicted accent on the target-bearing word. Acoustic analyses revealed greater F0 range in the preceding intonation of the predicted-accent sentences. These findings have implications for how universal and language-specific mechanisms interact in the processing of salience.

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

Listeners' recognition of spoken language involves complex decoding processes: The continuous speech stream must be segmented into its component words, and words must be recognized despite great variability in their pronunciation (due to talker differences, or to influence of phonetic context, or to speech register) and despite competition from many spuriously present forms supported by the speech signal. L1 listeners deal more readily with all levels of this complexity than L2 listeners. Fortunately, the decoding processes necessary for competent L2 listening can be taught in the classroom. Evidence-based methodologies targeted at the development of efficient speech decoding include teaching of minimal pairs, of phonotactic constraints, and of reduction processes, as well as the use of dictation and L2 video captions.

Abstract

Brain-to-brain interfaces, in which brains are physically connected without the intervention of language, promise new ways of collaboration and communication between humans. I examine the narrow view of language implicit in current conceptions of brain-to-brain interfaces and put forward a constructive alternative, stressing the role of language in organising joint agency. Two features of language stand out as crucial: its selectivity, which provides people with much-needed filters between public words and private worlds; and its negotiability, which provides people with systematic opportunities for calibrating understanding and expressing consent and dissent. Without these checks and balances, brain-to-brain interfaces run the risk of reducing people to the level of amoeba in a slime mold; with them, they may mature to become useful extensions of human agency

Abstract

In conversation, people regularly deal with problems of speaking, hearing, and understanding. We report on a cross-linguistic investigation of the conversational structure of other-initiated repair (also known as collaborative repair, feedback, requests for clarification, or grounding sequences). We take stock of formats for initiating repair across languages (comparable to English huh?, who?, y’mean X?, etc.) and find that different languages make available a wide but remarkably similar range of linguistic resources for this function. We exploit the patterned variation as evidence for several underlying concerns addressed by repair initiation: characterising trouble, managing responsibility, and handling knowledge. The concerns do not always point in the same direction and thus provide participants in interaction with alternative principles for selecting one format over possible others. By comparing conversational structures across languages, this paper contributes to pragmatic typology: the typology of systems of language use and the principles that shape them.

Abstract

Linguistic discovery is viewpoint-dependent, just like our ideas about what is marginal and what is central in language. In this essay I consider two supposed marginalia —ideophones and interjections— which provide some useful pointers for widening our field of view. Ideophones challenge us to take a fresh look at language and consider how it is that our communication system combines multiple modes of representation. Interjections challenge us to extend linguistic inquiry beyond sentence level, and remind us that language is social-interactive at core. Marginalia, then, are not the obscure, exotic phenomena that can be safely ignored: they represent opportunities for innovation and invite us to keep pushing the edges of linguistic inquiry.

Abstract

Doing things for and with others is one of the foundations of human social life. This chapter studies a systematic collection of 207 requests for assistance and collaboration from a video corpus of everyday conversations in Siwu, a Kwa language of Ghana. A range of social action formats and semiotic resources reveals how language is adapted to the interactional challenges posed by recruiting assistance. While many of the formats bear a language-specific signature, their sequential and interactional properties show important commonalities across languages. Two tentative findings are put forward for further cross-linguistic examination: a “rule of three” that may play a role in the organisation of successive response pursuits, and a striking commonality in animal-oriented recruitments across languages that may be explained by convergent cultural evolution. The Siwu recruitment system emerges as one instance of a sophisticated machinery for organising collaborative action that transcends language and culture.

Abstract

Responding to similarity, difference, and relative magnitude (SDM) is ubiquitous in the animal kingdom. However, humans seem unique in the ability to represent relative magnitude (‘more’/‘less’) and similarity (‘same’/‘different’) as abstract relations that take arguments (e.g., greater-than (x,y)). While many models use structured relational representations of magnitude and similarity, little progress has been made on how these representations arise. Models that developuse these representations assume access to computations of similarity and magnitude a priori, either encoded as features or as output of evaluation operators. We detail a mechanism for producing invariant responses to “same”, “different”, “more”, and “less” which can be exploited to compute similarity and magnitude as an evaluation operator. Using DORA (Doumas, Hummel, & Sandhofer, 2008), these invariant responses can serve be used to learn structured relational representations of relative magnitude and similarity from pixel images of simple shapes

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

We report the results of a large-scale (N=1571) experiment to investigate whether spoken words can emerge from the process of repeated imitation. Participants played a version of the children’s game “Telephone”. The first generation was asked to imitate recognizable environmental sounds (e.g., glass breaking, water splashing); subsequent generations imitated the imitators for a total of 8 generations. We then examined whether the vocal imitations became more stable and word-like, retained a resemblance to the original sound, and became more suitable as learned category labels. The results showed (1) the imitations became progressively more word-like, (2) even after 8 generations, they could be matched above chance to the environmental sound that motivated them, and (3) imitations from later generations were more effective as learned category labels. These results show how repeated imitation can create progressively more word-like forms while retaining a semblance of iconicity.

Abstract

This chapter reviews the computational processes that are responsible for recognizing word forms in the speech stream. We outline the different stages in a processing hierarchy from the extraction of general acoustic features, through speech‐specific prelexical processes, to the retrieval and selection of lexical representations. We argue that two recurring properties of the system as a whole are abstraction and adaptability. We also present evidence for parallel processing of information on different timescales, more specifically that segmental material in the speech stream (its consonants and vowels) is processed in parallel with suprasegmental material (the prosodic structures of spoken words). We consider evidence from both psycholinguistics and neurobiology wherever possible, and discuss how the two fields are beginning to address common computational problems. The challenge for future research in speech perception will be to build an account that links these computational problems, through functional mechanisms that address them, to neurobiological implementation.

Abstract

Anaphora, a ubiquitous feature of natural language, poses a particular challenge to young children as they first learn language due to its referential ambiguity. In spite of this, parents and caregivers use anaphora frequently in child-directed speech, potentially presenting a risk to effective communication if children do not yet have the linguistic capabilities of resolving anaphora successfully. Through an eye-tracking study in a naturalistic free-play context, we examine the strategies that parents employ to calibrate their use of anaphora to their child's linguistic development level. We show that, in this way, parents are able to intuitively scaffold the complexity of their speech such that greater referential ambiguity does not hurt overall communication success.

Abstract

The Cha’palaa language of Ecuador (Barbacoan) features verbal morphology for marking knowledge-based categories that, in usage, show a variant of the cross-linguistically recurrent pattern of ‘egophoric distribution': specific forms associate with speakers in contrast to others in statements and with addressees in contrast to others in questions. These are not person markers, but rather are used by speakers to portray their involvement in states of affairs as active, agentive participants (ego) versus other types of involvement (non-ego). They interact with person and argument structure, but through pragmatic ‘person sensitivities’ rather than through grammatical agreement. Not only does this pattern appear in verbal morphology, it also can be observed in alternations of predicate construction types and case alignment, helping to show how egophoric marking is a pervasive element of Cha'palaa's linguistic system. This chapter gives a first account of egophoricity in Cha’palaa, beginning with a discussion of person sensitivity, egophoric distribution, and issues of flexibility of marking with respect to degree of volition or control. It then focuses on a set of intransitive experiencer (or ‘endopathic') predicates that refer to internal states which mark egophoric values for the undergoer role, not the actor role, showing ‘quirky’ accusative marking instead of nominative case. It concludes with a summary of how egophoricity in Cha'palaa interacts with issues of argument structure in comparison to a language with person agreement, here represented by examples from Cha’palaa’s neighbor Ecuadorian Highland Quechua.

Abstract

Structural imaging based on computerized tomography (CT) and magnetic resonance imaging (MRI) has progressively replaced traditional post‐mortem studies in the process of identifying the neuroanatomical basis of language. In the clinical setting, the information provided by structural imaging has been used to confirm the exact diagnosis and formulate an individualized treatment plan. In the research arena, neuroimaging has permitted to understand neuroanatomy at the individual and group level. The possibility to obtain quantitative measures of lesions has improved correlation analyses between severity of symptoms, lesion load, and lesion location. More recently, the development of structural imaging based on diffusion MRI has provided valid solutions to two major limitations of more conventional imaging. In stroke patients, diffusion can visualize early changes due to a stroke that are otherwise not detectable with more conventional structural imaging, with important implications for the clinical management of acute stroke patients. Beyond the sensitivity to early changes, diffusion imaging tractography presents the possibility of visualizing the trajectories of individual white matter pathways connecting distant regions. A pathway analysis based on tractography is offering a new perspective in neurolinguistics. First, it permits to formulate new anatomical models of language function in the healthy brain and allows to directly test these models in the human population without any reliance on animal models. Second, by defining the exact location of the damage to specific white matter connections we can understand the contribution of different mechanisms to the emergence of language deficits (e.g., cortical versus disconnection mechanisms). Finally, a better understanding of the anatomical variability of different language networks is helping to identify new anatomical predictors of language recovery. In this chapter we will focus on the principles of structural MRI and, in particular, diffusion imaging and tractography and present examples of how these methods have informed our understanding of variance in language performances in the healthy brain and language deficits in patient populations.

Abstract

As knowing a foreign language becomes a necessity in the modern world, a large portion of
the population is faced with the challenge of learning a language in a classroom. This, in turn,
presents a unique set of difficulties. Acquiring a language with limited and artificial exposure makes
learning new information and vocabulary particularly difficult. The purpose of this thesis is to help us
understand how we can compensate—at least partially—for these difficulties by presenting
information in a way that aids learning. In particular, I focused on variables that affect semantic
richness—meaning the amount and variability of information associated with a word. Some factors
that affect semantic richness are intrinsic to the word and others pertain to that word’s relationship
with other items and information. This latter group depends on the context around the to-be-
learned items rather than the words themselves. These variables are easier to manipulate than
intrinsic qualities, making them more accessible tools for teaching and understanding learning. I
focused on two factors: emotionality of the surrounding semantic context and contextual diversity.
Publication 1 (Frances, de Bruin, et al., 2020b) focused on content learning in a foreign
language and whether the emotionality—positive or neutral—of the semantic context surrounding
key information aided its learning. This built on prior research that showed a reduction in
emotionality in a foreign language. Participants were taught information embedded in either
positive or neutral semantic contexts in either their native or foreign language. When they were
then tested on these embedded facts, participants’ performance decreased in the foreign language.
But, more importantly, they remembered better the information from the positive than the neutral
semantic contexts.
In Publication 2 (Frances, de Bruin, et al., 2020a), I focused on how emotionality affected
vocabulary learning. I taught participants the names of novel items described either in positive or
neutral terms in either their native or foreign language. Participants were then asked to recall and
recognize the object's name—when cued with its image. The effects of language varied with the
difficulty of the task—appearing in recall but not recognition tasks. Most importantly, learning the
words in a positive context improved learning, particularly of the association between the image of
the object and its name.
In Publication 3 (Frances, Martin, et al., 2020), I explored the effects of contextual
diversity—namely, the number of texts a word appears in—on native and foreign language word
learning. Participants read several texts that had novel pseudowords. The total number of
encounters with the novel words was held constant, but they appeared in 1, 2, 4, or 8 texts in either
their native or foreign language. Increasing contextual diversity—i.e., the number of texts a word
appeared in—improved recall and recognition, as well as the ability to match the word with its
meaning. Using a foreign language only affected performance when participants had to quickly
identify the meaning of the word.
Overall, I found that the tested contextual factors related to semantic richness—i.e.,
emotionality of the semantic context and contextual diversity—can be manipulated to improve
learning in a foreign language. Using positive emotionality not only improved learning in the foreign
language, but it did so to the same extent as in the native language. On a theoretical level, this
suggests that the reduction in emotionality in a foreign language is not ubiquitous and might relate
to the way in which that language as learned.
The third article shows an experimental manipulation of contextual diversity and how this
can affect learning of a lexical item, even if the amount of information known about the item is kept
constant. As in the case of emotionality, the effects of contextual diversity were also the same
between languages. Although deducing words from context is dependent on vocabulary size, this
does not seem to hinder the benefits of contextual diversity in the foreign language.
Finally, as a whole, the articles contained in this compendium provide evidence that some
aspects of semantic richness can be manipulated contextually to improve learning and memory. In
addition, the effects of these factors seem to be independent of language status—meaning, native
or foreign—when learning new content. This suggests that learning in a foreign and a native
language is not as different as I initially hypothesized, allowing us to take advantage of native
language learning tools in the foreign language, as well.

Abstract

One of the most daunting tasks of a listener is to map a
continuous auditory stream onto known speech sound
categories and lexical items. A major issue with this mapping
problem is the variability in the acoustic realizations of sound
categories, both within and across speakers. Past research has
suggested listeners may use visual information (e.g., lipreading)
to calibrate these speech categories to the current
speaker. Previous studies have focused on audiovisual
recalibration of consonant categories. The present study
explores whether vowel categorization, which is known to show
less sharply defined category boundaries, also benefit from
visual cues.
Participants were exposed to videos of a speaker
pronouncing one out of two vowels, paired with audio that was
ambiguous between the two vowels. After exposure, it was
found that participants had recalibrated their vowel categories.
In addition, individual variability in audiovisual recalibration is
discussed. It is suggested that listeners’ category sharpness may
be related to the weight they assign to visual information in
audiovisual speech perception. Specifically, listeners with less
sharp categories assign more weight to visual information
during audiovisual speech recognition.

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

Language acquisition is complex. However, one thing that has been suggested to help learning is the way that information is distributed throughout language; co-occurrences among particular items (e.g., syllables and words) have been shown to help learners discover the words that a language contains and figure out how those words are used. Humans’ ability to draw on this information—“statistical learning”—has been demonstrated across a broad range of studies. However, evidence from non-WEIRD (Western, Educated, Industrialized, Rich, and Democratic) societies is critically lacking, which limits theorizing on the universality of this skill. We extended work on statistical language learning to a new, non-WEIRD linguistic population: speakers of Yélî Dnye, who live on a remote island off mainland Papua New Guinea (Rossel Island). We performed a replication of an existing statistical learning study, training adults on an artificial language with statistically defined words, then examining what they had learnt using a two-alternative forced-choice test. Crucially, we implemented several key amendments to the original study to ensure the replication was suitable for remote field-site testing with speakers of Yélî Dnye. We made critical changes to the stimuli and materials (to test speakers of Yélî Dnye, rather than English), the instructions (we re-worked these significantly, and added practice tasks to optimize participants’ understanding), and the study format (shifting from a lab-based to a portable tablet-based setup). We discuss the requirement for acute sensitivity to linguistic, cultural, and environmental factors when adapting studies to test new populations.

Abstract

Acquiring language is notoriously complex, yet for the majority of children this feat is accomplished with remarkable ease. Usage-based accounts of language acquisition suggest that this success can be largely attributed to the wealth of experience with language that children accumulate over the course of language acquisition. One field of research that is heavily underpinned by this principle of experience is statistical learning, which posits that learners can perform powerful computations over the distribution of information in a given input, which can help them to discern precisely how that input is structured, and how it operates. A growing body of work brings this notion to bear in the field of language acquisition, due to a developing understanding of the richness of the statistical information contained in speech. In this chapter we discuss the role that statistical learning plays in language acquisition, emphasising the importance of both the distribution of information within language, and the situation in which language is being learnt. First, we address the types of statistical learning that apply to a range of language learning tasks, asking whether the statistical processes purported to support language learning are the same or distinct across different tasks in language acquisition. Second, we expand the perspective on what counts as environmental input, by determining how statistical learning operates over the situated learning environment, and not just sequences of sounds in utterances. Finally, we address the role of variability in children’s input, and examine how statistical learning can accommodate (and perhaps even exploit) this during language acquisition.

Abstract

A crucial aspect of everyday conversational interactions is our ability to establish and maintain common ground. Understanding the relevant mechanisms involved in such social coordination remains an important challenge for cognitive science. While common ground is often discussed in very general terms, different contexts of interaction are likely to afford different coordination mechanisms. In this paper, we investigate the presence and relation of three mechanisms of social coordination – backchannels, interactive alignment and conversational repair – across free and task-oriented conversations. We find significant differences: task-oriented conversations involve higher presence of repair – restricted offers in particular – and backchannel, as well as a reduced level of lexical and syntactic alignment. We find that restricted repair is associated with lexical alignment and open repair with backchannels. Our findings highlight the need to explicitly assess several mechanisms at once and to investigate diverse activities to understand their role and relations.

Abstract

Graph neural networks (GNNs) have emerged as the standard method for numerous tasks on graph-structured data such as node classification. However, real-world graphs are often evolving over time and even new classes may arise. We model these challenges as an instance of lifelong learning, in which a learner faces a sequence of tasks and may take over knowledge acquired in past tasks. Such knowledge may be stored explicitly as historic data or implicitly within model parameters. In this work, we systematically analyze the influence of implicit and explicit knowledge. Therefore, we present an incremental training method for lifelong learning on graphs and introduce a new measure based on k-neighborhood time differences to address variances in the historic data. We apply our training method to five representative GNN architectures and evaluate them on three new lifelong node classification datasets. Our results show that no more than 50% of the GNN's receptive field is necessary to retain at least 95% accuracy compared to training over the complete history of the graph data. Furthermore, our experiments confirm that implicit knowledge becomes more important when fewer explicit knowledge is available.

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

COVID-19 research datasets are crucial for analyzing research dynamics. Most collections of COVID-19 research items do not to include cited works and do not have annotations
from a controlled vocabulary. Starting with ZB MED KE data on COVID-19, which comprises CORD-19, we assemble a new dataset that includes cited work and MeSH annotations for all records. Furthermore, we conduct experiments on the analysis of research dynamics, in which we investigate predicting links in a co-annotation graph created on the basis of the new dataset. Surprisingly, we find that simple heuristic methods are better at
predicting future links than more sophisticated approaches such as 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 conduct the first systematic comparison of automated semantic
annotation based on either the full-text or only on the title metadata
of documents. Apart from the prominent text classification baselines
kNN and SVM, we also compare recent techniques of Learning
to Rank and neural networks and revisit the traditional methods
logistic regression, Rocchio, and Naive Bayes. Across three of our
four datasets, the performance of the classifications using only titles
reaches over 90% of the quality compared to the performance when
using the full-text.

Abstract

We assess the suitability of word embeddings for practical information retrieval scenarios. Thus, we assume that users issue ad-hoc short queries where we return the first twenty retrieved documents after applying a boolean matching operation between the query and the documents. We compare the performance of several techniques that leverage word embeddings in the retrieval models to compute the similarity between the query and the documents, namely word centroid similarity, paragraph vectors, Word Mover’s distance, as well as our novel inverse document frequency (IDF) re-weighted word centroid similarity. We evaluate the performance using the ranking metrics mean average precision, mean reciprocal rank, and normalized discounted cumulative gain. Additionally, we inspect the retrieval models’ sensitivity to document length by using either only the title or the full-text of the documents for the retrieval task. We conclude that word centroid similarity is the best competitor to state-of-the-art retrieval models. It can be further improved by re-weighting the word frequencies with IDF before aggregating the respective word vectors of the embedding. The proposed cosine similarity of IDF re-weighted word vectors is competitive to the TF-IDF baseline and even outperforms it in case of the news domain with a relative percentage of 15%.

Abstract

Reading is a cultural invention that needs to recruit cortical infrastructure that was not designed for it (cultural recycling of cortical maps). In the case of reading both visual cortex and networks for speech processing are recruited. Here I discuss current views on the neurobiological underpinnings of spoken language that deviate in a number of ways from the classical Wernicke-Lichtheim-Geschwind model. More areas than Broca’s and Wernicke’s region are involved in language. Moreover, a division along the axis of language production and language comprehension does not seem to be warranted. Instead, for central aspects of language processing neural infrastructure is shared between production and comprehension. Arguments are presented in favor of a dynamic network view, in which the functionality of a region is co-determined by the network of regions in which it is embedded at particular moments in time. Finally, core regions of language processing need to interact with other networks (e.g. the attentional networks and the ToM network) to establish full functionality of language and communication. The consequences of this architecture for reading are discussed.