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

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 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

Dutch and English listeners’ perception of English words with partially overlapping onsets (e.g., accident- execute) was investigated. Partially overlapping words remained active longer for nonnative listeners, causing an increase of lexical competition in nonnative compared with native listening.

Abstract

Research on second language acquisition typically focuses on how a first language (L1) influences a second language (L2) in different linguistic domains and across modalities. This dissertation, in contrast, explores interactions between languages in the mind of a language learner by asking 1) can an emerging L2 influence an established L1? 2) if so, how is such influence realized? 3) are there parallel influences of the L1 on the L2? These questions were investigated for the expression of Manner (e.g. climb, roll) and Path (e.g. up, down) of motion, areas where substantial crosslinguistic differences exist in speech and co-speech gesture. Japanese and English are typologically distinct in this domain; therefore, narrative descriptions of four motion events were elicited from monolingual Japanese speakers (n=16), monolingual English speakers (n=13), and native Japanese speakers with intermediate knowledge of English (narratives elicited in both their L1 and L2, n=28). Ways in which Path and Manner were expressed at the lexical, syntactic, and gestural levels were analyzed in monolingual and non-monolingual production. Results suggest mutual crosslinguistic influences. In their L1, native Japanese speakers with knowledge of English displayed both Japanese- and English-like use of morphosyntactic elements to express Path and Manner (i.e. a combination of verbs and other constructions). Consequently, non-monolingual L1 discourse contained significantly more Path expressions per clause, with significantly greater mention of Goal of motion than monolingual Japanese and English discourse. Furthermore, the gestures of non-monolingual speakers diverged from their monolingual counterparts with differences in depiction of Manner and gesture perspective (character versus observer). Importantly, non-monolingual production in the L1 was not ungrammatical, but simply reflected altered preferences. As for L2 production, many effects of L1 influence were seen, crucially in areas parallel to those described above. Overall, production by native Japanese speakers who knew English differed from that of monolingual Japanese and English speakers. But L1 and L2 production within non-monolingual individuals was similar. These findings imply a convergence of L1-L2 linguistic systems within the mind of a language learner. Theoretical and methodological implications for SLA research and language assessment with respect to the ‘native speaker standard language’ are discussed.

Abstract

This paper investigates the prosodic realization of information
structure categories in Standard Chinese. A number of proper
names with different tonal combinations were elicited as a
grammatical subject in five pragmatic contexts. Results show
that both duration and F0 range of the tonal realizations were
adjusted to signal the information structure categories (i.e.
theme vs. rheme and background vs. focus). Rhemes
consistently induced a longer duration and a more expanded F0
range than themes. Focus, compared to background, generally
induced lengthening and F0 range expansion (the presence and
magnitude of which, however, are dependent on the tonal
structure of the proper names). Within the rheme focus
condition, corrective rheme focus induced more expanded F0
range than normal rheme focus.

Abstract

This study set out to investigate how accent placement is pragmatically governed in WH-questions. Central to this issue are questions such as whether the intonation of the WH-word depends on the information structure of the non-WH word part, whether topical constituents can be accented, and whether constituents in the non-WH word part can be non-topical and accented. Previous approaches, based either on carefully composed examples or on read speech, differ in their treatments of these questions and consequently make opposing claims on the intonation of WH-questions. We addressed these questions by examining a corpus of 90 naturally occurring WH-questions, selected from the Spoken Dutch Corpus. Results show that the intonation of the WH-word is related to the information structure of the non-WH word part. Further, topical constituents can get accented and the accents are not necessarily phonetically reduced. Additionally, certain adverbs, which have no topical relation to the presupposition of the WH-questions, also get accented. They appear to function as a device for enhancing speaker engagement.

Abstract

This paper describes hardware and software that can be used for the phonetic study of sign languages. The field of sign language phonetics is characterised, and the hardware that is currently in use is described. The paper focuses on the software that was developed to enable the recording of finger and hand movement data, and the additions to the ELAN annotation software that facilitate the further visualisation and analysis of the data.

Abstract

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

Abstract

Language-specific procedures which are efficient for listening to the L1 may be applied to non-native spoken input, often to the detriment of successful listening. However, such misapplications of L1-based listening do not always happen. We propose, based on the results from two experiments in which Japanese listeners detected target sequences in spoken Korean, that an L1 procedure is only triggered if requisite L1 features are present in the input.

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

Experiments have revealed differences across languages in listeners’ use of stress information in recognising spoken words. Previous comparisons of the vocabulary of Spanish and English had suggested that the explanation of this asymmetry might lie in the extent to which considering stress in spokenword recognition allows rejection of unwanted competition from words embedded in other words. This hypothesis was tested on the vocabularies of Dutch and German, for which word recognition results resemble those from Spanish more than those from English. The vocabulary statistics likewise revealed that in each language, the reduction of embeddings resulting from taking stress into account is more similar to the reduction achieved in Spanish than in English.

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

The Recent Out-of-Africa human evolutionary model seems to be generally accepted. This impression is very prevalent outside palaeoanthropological circles (including studies of language evolution), but proves to be unwarranted. This paper offers a short review of the main challenges facing ROA and concludes that alternative models based on the concept of metapopulation must be also considered. The implications of such a model for language evolution and diversity are briefly reviewed.

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

During listening to spoken language, the perceptual system needs to adapt frequently to changes in talkers, and thus to considerable interindividual variability in the articulation of a given speech sound. This thesis investigated a learning process which allows listeners to use stored lexical representations to modify the interpretation of a speech sound when a talker's articulation of that sound is consistently unclear or ambiguous. The questions that were addressed in this research concerned the robustness of such perceptual learning, a potential role for sleep, and whether learning is specific to the speech of one talker or, alternatively, generalises to other talkers. A further study aimed to identify the underlying functional neuroanatomy by using magnetic resonance imaging methods. The picture that emerged for lexically-guided perceptual learning is that learning occurs very rapidly, is highly specific, and remains remarkably robust both over time and under exposure to speech from other talkers.

Abstract

This paper examines code and style shifting during sales transactions based on two market case studies from highland Ecuador. Bringing together ideas of linguistic economy with work on stylistic variation and ethnohistorical research on Andean markets, I study bartering, market calls and sales pitches to show how sellers create stylistic performances distinguished by contrasts of code, register and poetic features. The interaction of the symbolic value of language with the economic values of the market presents a place to examine the relationship between discourse and the material world.

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

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

Abstract

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

Abstract

The aim of this paper is to explore whether indexing terms for an audiovisual program can be derived from contextual texts automatically. For this we apply natural-language processing techniques to contextual texts of two Dutch TV-programs. We use a Dutch domain thesaurus to derive possible metadata. This possible metadata is ranked by an algorithm which uses the relations of the thesaurus. We evaluate the results by comparing them to human made descriptions.

Abstract

Acquiring the sounds of a language involves learning to recognize distributional patterns present in the input. We show that among adult learners, this distributional learning of auditory categories (which are conceived of here as probability density functions in a multidimensional space) is constrained by the salience of the dimensions that form the axes of this perceptual space. Only with a particular ratio of variation in the perceptual dimensions was category learning driven by the distributional properties of the input.

Abstract

Many current sentence generators lack the ability to compute elliptical versions of coordinated clauses in accordance with the rules for Gapping, Forward and Backward Conjunction Reduction, and SGF (Subject Gap in clauses with Finite/ Fronted verb). We describe a module (implemented in JAVA, with German and Dutch as target languages) that takes non-elliptical coordinated clauses as input and returns all reduced versions licensed by coordinative ellipsis. It is loosely based on a new psycholinguistic theory of coordinative ellipsis proposed by Kempen. In this theory, coordinative ellipsis is not supposed to result from the application of declarative grammar rules for clause formation but from a procedural component that interacts with the sentence generator and may block the overt expression of certain constituents.

Abstract

We describe a generation-oriented workbench for the Performance Grammar (PG) formalism, highlighting the treatment of certain word order and movement constraints in Dutch and German. PG enables a simple and uniform treatment of a heterogeneous collection of linear order phenomena in the domain of verb constructions (variably known as Cross-serial Dependencies, Verb Raising, Clause Union, Extraposition, Third Construction, Particle Hopping, etc.). The central data structures enabling this feature are clausal “topologies”: one-dimensional arrays associated with clauses, whose cells (“slots”) provide landing sites for the constituents of the clause. Movement operations are enabled by unification of lateral slots of topologies at adjacent levels of the clause hierarchy. The PGW generator assists the grammar developer in testing whether the implemented syntactic knowledge allows all and only the well-formed permutations of constituents.

Abstract

There is evidence that the process of executing a planned utterance involves the use of both preceding-context and top-down cues. Utterance-initial words are cued only by the top-down plan. In contrast, non-initial words are cued both by top-down cues and preceding-context cues. Co-existence of both cue types raises the question of how they interact during learning. We argue that this interaction is competitive: items that tend to be preceded by predictive preceding-context cues are harder to activate from the plan without this predictive context. A novel computational model of this competition is developed. The model is tested on a corpus of repetition disfluencies and shown to account for the influences on patterns of restarts during production. In particular, this model predicts a novel Initiation Effect: following an interruption, speakers re-initiate production from words that tend to occur in utterance-initial position, even when they are not initial in the interrupted utterance.

Abstract

The representations generated by many mod-
els of language (word embeddings, recurrent
neural networks and transformers) correlate
to brain activity recorded while people read.
However, these decoding results are usually
based on the brain’s reaction to syntactically
and semantically sound language stimuli. In
this study, we asked: how does an LSTM (long
short term memory) language model, trained
(by and large) on semantically and syntac-
tically intact language, represent a language
sample with degraded semantic or syntactic
information? Does the LSTM representation
still resemble the brain’s reaction? We found
that, even for some kinds of nonsensical lan-
guage, there is a statistically significant rela-
tionship between the brain’s activity and the
representations of an LSTM. This indicates
that, at least in some instances, LSTMs and the
human brain handle nonsensical data similarly.

Abstract

Longitudinally collected VOT data from an early English-Italian bilingual who became increasingly English-dominant was analyzed. Stops in English were always produced with significantly longer VOT than in Italian. However, the speaker did not show any significant change in the VOT production in either language over time, despite the clear dominance of English in his every day language use later in his life. The results indicate that – unlike L2 learners – early bilinguals may remain unaffected by language use with respect to phonetic realization.

Abstract

What makes some words harder to learn than others in a second language? Although some robust factors have been identified based on small scale experimental studies, many relevant factors are difficult to study in such experiments due to the amount of data necessary to test them. Here, we investigate what factors affect the ease of learning of a word in a second language using a large data set of users learning English as a second language through the Duolingo mobile app. In a regression analysis, we test and confirm the well-studied effect of cognate status on word learning accuracy. Furthermore, we find significant effects for both cross-linguistic semantic alignment and English semantic density, two novel predictors derived from large scale distributional models of lexical semantics. Finally, we provide data on several other psycholinguistically plausible word level predictors. We conclude with a discussion of the limits, benefits and future research potential of using big data for investigating second language learning.

Abstract

A common assumption in the cognitive sciences is that artificial and natural language learning rely on shared mechanisms. However, attempts to bridge the two have yielded ambiguous results. We suggest that an empirical disconnect between the computations employed during learning and the methods employed at test may explain these mixed results. Further, we propose statistically-based chunking as a potential computational link between artificial and natural language learning. We compare the acquisition of non-adjacent dependencies to that of natural language structure using two types of tasks: reflection-based 2AFC measures, and processing-based recall measures, the latter being more computationally analogous to the processes used during language acquisition. Our results demonstrate that task-type significantly influences the correlations observed between artificial and natural language acquisition, with reflection-based and processing-based measures correlating within – but not across – task-type. These findings have fundamental implications for artificial-to-natural language comparisons, both methodologically and theoretically.

Abstract

It has been suggested that some individuals may benefit more from social robots than do others. Using second
language (L2) as an example, the present study examined how individual differences in attitudes toward robots and personality
traits may be related to learning outcomes. Preliminary results with 24 Turkish-speaking adults suggest that negative attitudes
toward robots, more specifically thoughts and anxiety about the negative social impact that robots may have on the society,
predicted how well adults learned L2 words from a social robot. The possible implications of the findings as well as future directions are also discussed

Abstract

A central question in the psycholinguistic study of multilingualism is how syntax is shared across languages. We implement a model to investigate whether error-based implicit learning can provide an account of cross-language structural priming. The model is based on the Dual-path model of
sentence-production (Chang, 2002). We implement our model using the Bilingual version of Dual-path (Tsoukala, Frank, & Broersma, 2017). We answer two main questions: (1) Can structural priming of active and passive constructions occur between English and Spanish in a bilingual version of the Dual-
path model? (2) Does cross-language priming differ quantitatively from within-language priming in this model? Our results show that cross-language priming does occur in the model. This finding adds to the viability of implicit learning as an account of structural priming in general and cross-language
structural priming specifically. Furthermore, we find that the within-language priming effect is somewhat stronger than the cross-language effect. In the context of mixed results from
behavioral studies, we interpret the latter finding as an indication that the difference between cross-language and within-
language priming is small and difficult to detect statistically.