Publications

Abstract

Language evolution can be viewed from two viewpoints: the development of a communicative system and the biological adaptations necessary for producing and perceiving said system. The communicative-system vantage point has enjoyed a wealth of mathematical models based on simple distributional properties of language, often formulated as empirical laws. However, be- yond vague psychological notions of “least effort”, no principled explanation has been proposed for the existence and success of such laws. Meanwhile, psychological and neurobiological mod- els have focused largely on the computational constraints presented by incremental, real-time processing. In the following, we show that information-theoretic entropy underpins successful models of both types and provides a more principled motivation for Zipf’s Law

Abstract

Experiments in Artificial Language Learn-
ing have revealed much about the cogni-
tive mechanisms underlying sequence and
language learning in human adults, in in-
fants and in non-human animals. This pa-
per focuses on their ability to generalize
to novel grammatical instances (i.e., in-
stances consistent with a familiarization
pattern). Notably, the propensity to gen-
eralize appears to be negatively correlated
with the amount of exposure to the artifi-
cial language, a fact that has been claimed
to be contrary to the predictions of statis-
tical models (Pe
̃
na et al. (2002); Endress
and Bonatti (2007)). In this paper, we pro-
pose to model generalization as a three-
step process, and we demonstrate that the
use of statistical models for the first two
steps, contrary to widespread intuitions in
the ALL-field, can explain the observed
decrease of the propensity to generalize
with exposure time.

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

In an influential paper, Marcus et al. [1999] claimed that connectionist models
cannot account for human success at learning tasks that involved generalization
of abstract knowledge such as grammatical rules. This claim triggered a heated
debate, centered mostly around variants of the Simple Recurrent Network model
[Elman, 1990]. In our work, we revisit this unresolved debate and analyze the
underlying issues from a different perspective. We argue that, in order to simulate
human-like learning of grammatical rules, a neural network model should not be
used as a
tabula rasa
, but rather, the initial wiring of the neural connections and
the experience acquired prior to the actual task should be incorporated into the
model. We present two methods that aim to provide such initial state: a manipu-
lation of the initial connections of the network in a cognitively plausible manner
(concretely, by implementing a “delay-line” memory), and a pre-training algorithm
that incrementally challenges the network with novel stimuli. We implement such
techniques in an Echo State Network [Jaeger, 2001], and we show that only when
combining both techniques the ESN is able to learn truly general identity rules.

Abstract

The present paper assesses discourse-pragmatic factors as a potential explanation for the subject-object assymetry in early child language. It identifies a set of factors which characterize typical situations of informativeness (Greenfield & Smith, 1976), and uses these factors to identify informative arguments in data from four children aged 2;0 through 3;6 learning Inuktitut as a first language. In addition, it assesses the extent of the links between features of informativeness on one hand and lexical vs. null and subject vs. object arguments on the other. Results suggest that a pragmatics account of the subject-object asymmetry can be upheld to a greater extent than previous research indicates, and that several of the factors characterizing informativeness are good indicators of those arguments which tend to be omitted in early child language.

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

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 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

Speakers use differential referring expressions in pragmatically appropriate ways to produce coherent narratives. Languages, however, differ in a) whether REs as arguments can be dropped and b) whether personal pronouns encode gender. We examine two languages that differ from each other in these two aspects and ask whether the co-reference context and the gender encoding options affect the use of REs differentially. We elicited narratives from Dutch and Turkish speakers about two types of three-person events, one including people of the same and the other of mixed-gender. Speakers re-introduced referents into the discourse with fuller forms (NPs) and maintained them with reduced forms (overt or null pronoun). Turkish speakers used pronouns mainly to mark emphasis and only Dutch speakers used pronouns differentially across the two types of videos. We argue that linguistic possibilities available in languages tune speakers into taking different principles into account to produce pragmatically coherent narratives

Abstract

In conversation, listeners frequently encounter speakers with foreign accents. Previous research on foreign-accented speech has primarily examined the short-term effects of exposure and the relative ease that listeners have with adapting to an accent. The present study examines the stability of this adaptation, with seven full days between testing sessions. On both days, subjects performed a cross-modal priming task in which they heard several minutes of an unfamiliar accent of their native language: a form of Hebrewaccented Dutch in which long /i:/ was shortened to /I/. During this task on Day 1, recognition of accented forms was not facilitated, compared to that of canonical forms. A week later, when tested on new words, facilitatory priming occurred, comparable to that seen for canonically produced items tested in both sessions. These results suggest that accented forms can be learned from brief exposure and the stable effects of this can be seen a week later.

Abstract

How does a naive language learner deal with speaker variation irrelevant to distinguishing word meanings? Experimental data is contradictory, and incompatible models have been proposed. Here, we examine basic assumptions regarding the acoustic signal the learner deals with: Is speaker variability a hurdle in discriminating sounds or can it easily be ignored? To this end, we summarize existing infant data. We then present machine-based discriminability scores of sound pairs obtained without any language knowledge. Our results show that speaker variability decreases sound contrast discriminability, and that some contrasts are affected more than others. However, chance performance is rare; most contrasts remain discriminable in the face of speaker variation. We take our results to mean that speaker variation is not a uniform hurdle to discriminating sound contrasts, and careful examination is necessary when planning and interpreting studies testing whether and to what extent infants (and adults) are sensitive to speaker differences.

Abstract

In the present paper we investigate the effect of categorising raw behavioural data or computational model responses. In addition, the effect of averaging over stimuli from potentially different populations is assessed. To this end, we replicate studies on word learning and generalisation abilities using the ACORNS models. Our results show that discrete categories may obscure interesting phenomena in the continuous responses. For example, the finding that learning in the model saturates very early at a uniform high recognition accuracy only holds for categorical representations. Additionally, a large difference in the accuracy for individual words is obscured by averaging over all stimuli. Because different words behaved differently for different speakers, we could not identify a phonetic basis for the differences. Implications and new predictions for infant behaviour are discussed.

Abstract

In the present paper we investigate the effect of categorising raw behavioural data or computational model responses. In addition, the effect of averaging over stimuli from potentially different populations is assessed. To this end, we replicate studies on word learning and generalisation abilities using the ACORNS models. Our results show that discrete
categories may obscure interesting phenomena in the continuous
responses. For example, the finding that learning in the model saturates very early at a uniform high recognition accuracy only holds for categorical representations. Additionally, a large difference in the accuracy for individual words is obscured
by averaging over all stimuli. Because different words behaved
differently for different speakers, we could not identify a phonetic
basis for the differences. Implications and new predictions for
infant behaviour are discussed.

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

During conversation, spoken utterances occur in rich acoustic contexts, including speech produced by our interlocutor(s) and speech we produced ourselves. Prosodic characteristics of the acoustic context have been known to influence speech perception in a contrastive fashion: for instance, a vowel presented in a fast context is perceived to have a longer duration than the same vowel in a slow context. Given the ubiquity of the sound of our own voice, it may be that our own speech rate - a common source of acoustic context - also influences our perception of the speech of others. Two experiments were designed to test this hypothesis. Experiment 1 replicated earlier contextual rate effects by showing that hearing pre-recorded fast or slow context sentences alters the perception of ambiguous Dutch target words. Experiment 2 then extended this finding by showing that talking at a fast or slow rate prior to the presentation of the target words also altered the perception of those words. These results suggest that between-talker variation in speech rate production may induce between-talker variation in speech perception, thus potentially explaining why interlocutors tend to converge on speech rate in dialogue settings.

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

Space and time appear to be related asymmetrically in the child’s mind: temporal representations depend on spatial representations more than vice versa, as predicted by space-time metaphors in language. In a study supporting this conclusion, spatial information interfered with children’s temporal judgments more than vice versa (Casasanto, Fotakopoulou, & Boroditsky, 2010, Cognitive Science). In this earlier study, however, spatial information was available to participants for more time than temporal information was (as is often the case when people observe natural events), suggesting a skeptical explanation for the observed effect. Here we conducted a stronger test of the hypothesized space-time asymmetry, controlling spatial and temporal aspects of the stimuli even more stringently than they are generally ’controlled’ in the natural world. Results replicated Casasanto and colleagues’, validating their finding of a robust representational asymmetry between space and time, and extending it to children (4-10 y.o.) who speak Dutch and Brazilian Portuguese.

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

Paper presented at The 161th Meeting Acoustical Society of America, Seattle, Washington, 23-27 May 2011. Reduction in casual speech can create ambiguity, e.g., “he was” can sound like “he’s.” Before quotative “like” “so she’s/she was like…”, it was found that there is little accurate acoustic information about the distinction in the signal. This work examines what types of information acoustics of the target itself, speech rate, coarticulation, and syntax/semantics listeners use to recognize such reduced function words. We compare perception studies presenting the targets auditorily with varying amounts of context, presenting the context without the targets, and a visual study presenting context in written form. Given primarily discourse information visual or auditory context only, subjects are strongly biased toward past, reflecting the use of quotative “like” for reporting past speech. However, if the target itself is presented, the direction of bias reverses, indicating that listeners favor acoustic information within the target which is reduced, sounding like the shorter, present form over almost any other source of information. Furthermore, when the target is presented auditorily with surrounding context, the bias shifts slightly toward the direction shown in the orthographic or auditory-no-target experiments. Thus, listeners prioritize acoustic information within the target when present, even if that information is misleading, but they also take discourse information into account.

Abstract

Listeners’ interactions often take place in auditorily challenging conditions. We examined how noise affects phonological competition during spoken word recognition. In a visual-world experiment, which allows us to examine the timecourse of recognition, English participants listened to target words in quiet and in noise while they saw four pictures on the screen: a target (e.g. candle), an onset overlap competitor (e.g. candy), an offset overlap competitor (e.g. sandal), and a distractor. The results showed that, while all competitors were relatively quickly suppressed in quiet listening conditions, listeners experienced persistent competition in noise from the offset competitor but not from the onset competitor. This suggests that listeners’ phonological competitor activation persists for longer in noise than in quiet and that listeners are able to deactivate some unwanted competition when listening to speech in noise. The well-attested competition pattern in quiet was not replicated. Possible methodological explanations for this result are discussed.

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

If concepts, categories, and word meanings are stable, how can people use them so flexibly? Here we explore a possible answer: maybe this stability is an illusion. Perhaps all concepts, categories, and word meanings (CC&Ms) are constructed ad hoc, each time we use them. On this proposal, all words are infinitely polysemous, all communication is ’good enough’, and no idea is ever the same twice. The details of people’s ad hoc CC&Ms are determined by the way retrieval cues interact with the physical, social, and linguistic context. We argue that even the most stable-seeming CC&Ms are instantiated via the same processes as those that are more obviously ad hoc, and vary (a) from one microsecond to the next within a given instantiation, (b) from one instantiation to the next within an individual, and (c) from person to person and group to group as a function of people’s experiential history. 826

Abstract

Can simple motor actions help people expand their vocabulary? Here we show that word learning depends on where students place their flash cards after studying them. In Experiment 1, participants learned the definitions of ”alien words” with positive or negative emotional valence. After studying each card, they placed it in one of two boxes (top or bottom), according to its valence. Participants who were instructed to place positive cards in the top box, consistent with Good is Up metaphors, scored about 10.

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

When we think of children acquiring language, we often think of their acquisition of linguistic structure as separate from their acquisition of knowledge about the world. But it is clear that in the process of learning about language, children consult what they know about the world; and that in learning about the world, children use linguistic cues to discover how items are related to one another. This interaction between the acquisition of linguistic structure and the acquisition of category structure is especially clear in word learning.

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

Pitch accents are analysed differently in an onramp analysis (i.e. ToBI) and an off-ramp analysis (e.g. Transcription of Dutch intonation - ToDI), two competing approaches in the Autosegmental Metrical tradition. A case in point is pre-final high rise. A pre-final rise is analysed as H* in ToBI but is phonologically ambiguous between H* or H*L (a (rise-)fall) in ToDI. This is because in ToDI, the L tone of a pre-final H*L can be realised in the following unaccented words and both H* and H*L can show up as a high rise in the accented word. To find out whether there is a two-way phonological contrast in pre-final high rises in Dutch, we examined the distribution of phonologically ambiguous high rises (H*(L)) and their phonetic realisation in different information structural conditions (topic vs. focus), compared to phonologically unambiguous H* and H*L. Results showed that there is indeed a H*L vs. H* contrast in prefinal high rises in Dutch and that H*L is realised as H*(L) when sonorant material is limited in the accented word. These findings provide new evidence for an off-ramp analysis of Dutch intonation and have far-reaching implications for analysis of intonation across languages.

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

Although people are poor at naming odors, naming a smell helps to remember that odor. Previous studies show wine experts have better memory for smells, and they also name smells differently than novices. Is wine experts’ odor memory is verbally mediated? And is the odor memory advantage that experts have over novices restricted to odors in their domain of expertise, or does it generalize? Twenty-four wine experts and 24 novices smelled wines, wine-related odors and common odors, and remembered these. Half the participants also named the smells. Wine experts had better memory for wines, but not for the other odors, indicating their memory advantage is restricted to wine. Wine experts named odors better than novices, but there was no relationship between experts’ ability to name odors and their memory for odors. This suggests experts’ odor memory advantage is not linguistically mediated, but may be the result of differential perceptual learning

Abstract

Assimilation of place of articulation across a nasal and a following stop consonant is obligatory in Japanese, but not in Dutch. In four experiments the processing of assimilated forms by speakers of Japanese and Dutch was compared, using a task in which listeners blended pseudo-word pairs such as ranga-serupa. An assimilated blend of this pair would be rampa, an unassimilated blend rangpa. Japanese listeners produced significantly more assimilated than unassimilated forms, both with pseudo-Japanese and pseudo-Dutch materials, while Dutch listeners produced significantly more unassimilated than assimilated forms in each materials set. This suggests that Japanese listeners, whose native-language phonology involves obligatory assimilation constraints, represent the assimilated nasals in nasal-stop sequences as unmarked for place of articulation, while Dutch listeners, who are accustomed to hearing unassimilated forms, represent the same nasal segments as marked for place of articulation.

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

To examine the relative roles of language-specific and language-universal mechanisms in the production of prosodic focus, we compared production of five different types of focus by native speakers of English and Mandarin. Two comparable dialogues were constructed for each language, with the same words appearing in focused and unfocused position; 24 speakers recorded each dialogue in each language. Duration, F0 (mean, maximum, range), and rms-intensity (mean, maximum) of all critical word tokens were measured. Across the different types of focus, cross-language differences were observed in the degree to which English versus Mandarin speakers use the different prosodic parameters to mark focus, suggesting that while prosody may be universally available for expressing focus, the means of its employment may be considerably language-specific

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

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

Languages contain tens of thousands of words, but these are constructed from a tiny handful of phonetic elements. Consequently, words resemble one another, or can be embedded within one another, a coup stick snot with standing. me process of spoken-word recognition by human listeners involves activation of multiple word candidates consistent with the input, and direct competition between activated candidate words. Further, human listeners are sensitive, at an early, prelexical, stage of speeeh processing, to constraints on what could potentially be a word of the language.

Abstract

Listeners performed speeded two-alternative choice between two unfamiliar and relatively similar voices or between two phonetically close segments, in VC syllables. For each decision type (segment, voice), the non-target dimension (voice, segment) either was constant, or varied across four alternatives. Responses were always slower when a non-target dimension varied than when it did not, but the effect of phonetic variation on voice identity decision was stronger than that of voice variation on phonetic identity decision. Cues to voice and segment identity in speech are processed inter-dependently, but hard categorization decisions about voices draw on, and are hence sensitive to, segmental information.

Abstract

The phoneme detection task is widely used in spoken word recognition research. Alphabetically literate participants, however, are more used to explicit representations of letters than of phonemes. The present study explored whether phoneme detection is sensitive to how target phonemes are, or may be, orthographically realised. Listeners detected the target sounds [b,m,t,f,s,k] in word-initial position in sequences of isolated English words. Response times were faster to the targets [b,m,t], which have consistent word-initial spelling, than to the targets [f,s,k], which are inconsistently spelled, but only when listeners’ attention was drawn to spelling by the presence in the experiment of many irregularly spelled fillers. Within the inconsistent targets [f,s,k], there was no significant difference between responses to targets in words with majority and minority spellings. We conclude that performance in the phoneme detection task is not necessarily sensitive to orthographic effects, but that salient orthographic manipulation can induce such sensitivity.

Abstract

Recently, there has been an explosion in the availability of large, good-quality cross-linguistic databases such as WALS (Dryer & Haspelmath, 2013), Glottolog (Hammarstrom et al., 2015) and Phoible (Moran & McCloy, 2014). Databases such as Phoible contain the actual segments used by various languages as they are given in the primary language descriptions. However, this segment-level representation cannot be used directly for analyses that require generalizations over classes of segments that share theoretically interesting features. Here we present a method and the associated R (R Core Team, 2014) code that allows the exible denition of such meaningful classes and that can identify the sets of segments falling into such a class for any language inventory. The method and its results are important for those interested in exploring cross-linguistic patterns of phonetic and phonological diversity and their relationship to extra-linguistic factors and processes such as climate, economics, history or human genetics.

Abstract

The current paper presents results for data on click learning obtained from a larger imaging study (using MRI and 3D intraoral scanning) designed to quantify and characterize intra- and inter-population variation of vocal tract structures and the relation of this to speech production. The aim of the click study was to ascertain whether and to what extent vocal tract morphology influences (1) the ability to learn to produce clicks and (2) the productions of those that successfully learn to produce these sounds. The results indicate that the presence of an alveolar ridge certainly does not prevent an individual from learning to produce click sounds (1). However, the subtle details of how clicks are produced may indeed be driven by palate shape (2).

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

Abstract mental representation is fundamental for human cognition. Forming such representations in time, especially from dynamic and noisy perceptual input, is a challenge for any processing modality, but perhaps none so acutely as for language processing. We show that LISA (Hummel & Holyaok, 1997) and DORA (Doumas, Hummel, & Sandhofer, 2008), models built to process and to learn structured (i.e., symbolic) rep resentations of conceptual properties and relations from unstructured inputs, show oscillatory activation during processing that is highly similar to the cortical activity elicited by the linguistic stimuli from Ding et al.(2016). We argue, as Ding et al.(2016), that this activation reflects formation of hierarchical linguistic representation, and furthermore, that the kind of computational mechanisms in LISA/DORA (e.g., temporal binding by systematic asynchrony of firing) may underlie formation of abstract linguistic representations in the human brain. It may be this repurposing that allowed for the generation or mergence of hierarchical linguistic structure, and therefore, human language, from extant cognitive and neural systems. We conclude that models of thinking and reasoning and models of language processing must be integrated —not only for increased plausiblity, but in order to advance both fields towards a larger integrative model of human cognition

Abstract

This paper summarizes the results of a descriptive syntactic category analysis of child English no which reveals that young children use and represent no as a determiner and negatives like no pen as NPs, contra standard analyses.

Abstract

Listeners use their lexical knowledge to interpret ambiguous sounds, and retune their phonetic categories to include this ambiguous sound. Although there is ample evidence for lexically-guided retuning, the adaptation process is not fully understood. Using a lexical decision task with an embedded auditory semantic priming task, the present study investigates whether words containing an ambiguous sound are processed in the same way as “natural” words and whether adaptation to the ambiguous sound tends to equalize the processing of “ambiguous” and natural words. Analyses of the yes/no responses and reaction times to natural and “ambiguous” words showed that words containing an ambiguous sound were accepted as words less often and were processed slower than the same words without ambiguity. The difference in acceptance disappeared after exposure to approximately 15 ambiguous items. Interestingly, lower acceptance rates and slower processing did not have an effect on the processing of semantic information of the following word. However, lower acceptance rates of ambiguous primes predict slower reaction times of these primes, suggesting an important role of stimulus-specific characteristics in triggering lexically-guided perceptual learning.

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

We investigated the use of Hidden Markov Models (HMMs) as a way of representing repertoires of continuous signals in order to infer their building blocks. We tested the idea on a dataset from an artificial language experiment. The study demonstrates using HMMs for this purpose is viable, but also that there is a lot of room for refinement such as explicit duration modeling, incorporation of autoregressive elements and relaxing the Markovian assumption, in order to accommodate specific details.

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 perception of danger in the environment can induce physiological responses (such as a heightened state of arousal) in animals, which may cause measurable changes in the prosodic modulation of the voice (Briefer, 2012). The ability to interpret the prosodic features of animal calls as an indicator of emotional arousal may have provided the first hominins with an adaptive advantage, enabling, for instance, the recognition of a threat in the surroundings. This ability might have paved the ability to process meaningful prosodic modulations in the emerging linguistic utterances.

Abstract

Humans combine multiple sources of information to comprehend meanings. These sources can be characterized as linguistic (i.e., lexical units and/or sentences) or paralinguistic (e.g. body posture, facial expression, voice intonation, pragmatic context). Emotion communication is a special case in which linguistic and paralinguistic dimensions can simultaneously denote the same, or multiple incongruous referential meanings. Think, for instance, about when someone says “I’m sad!”, but does so with happy intonation and a happy facial expression. Here, the communicative channels express very specific (although conflicting) emotional states as denotations. In such cases of intermodal incongruence, are we involuntarily biased to respond to information in one channel over the other? We hypothesize that humans are involuntary biased to respond to prosody over verbal content and facial expression, since the ability to communicate socially relevant information such as basic emotional states through prosodic modulation of the voice might have provided early hominins with an adaptive advantage that preceded the emergence of segmental speech (Darwin 1871; Mithen, 2005). To address this hypothesis, we examined the interaction between multiple communicative channels in recruiting attentional resources, within a Stroop interference task (i.e. a task in which different channels give conflicting information; Stroop, 1935). In experiment 1, we used synonyms of “happy” and “sad” spoken with happy and sad prosody. Participants were asked to identify the emotion expressed by the verbal content while ignoring prosody (Word task) or vice versa (Prosody task). Participants responded faster and more accurately in the Prosody task. Within the Word task, incongruent stimuli were responded to more slowly and less accurately than congruent stimuli. In experiment 2, we adopted synonyms of “happy” and “sad” spoken in happy and sad prosody, while a happy or sad face was displayed. Participants were asked to identify the emotion expressed by the verbal content while ignoring prosody and face (Word task), to identify the emotion expressed by prosody while ignoring verbal content and face (Prosody task), or to identify the emotion expressed by the face while ignoring prosody and verbal content (Face task). Participants responded faster in the Face task and less accurately when the two non-focused channels were expressing an emotion that was incongruent with the focused one, as compared with the condition where all the channels were congruent. In addition, in the Word task, accuracy was lower when prosody was incongruent to verbal content and face, as compared with the condition where all the channels were congruent. Our data suggest that prosody interferes with emotion word processing, eliciting automatic responses even when conflicting with both verbal content and facial expressions at the same time. In contrast, although processed significantly faster than prosody and verbal content, faces alone are not sufficient to interfere in emotion processing within a three-dimensional Stroop task. Our findings align with the hypothesis that the ability to communicate emotions through prosodic modulation of the voice – which seems to be dominant over verbal content - is evolutionary older than the emergence of segmental articulation (Mithen, 2005; Fitch, 2010). This hypothesis fits with quantitative data suggesting that prosody has a vital role in the perception of well-formed words (Johnson & Jusczyk, 2001), in the ability to map sounds to referential meanings (Filippi et al., 2014), and in syntactic disambiguation (Soderstrom et al., 2003). This research could complement studies on iconic communication within visual and auditory domains, providing new insights for models of language evolution. Further work aimed at how emotional cues from different modalities are simultaneously integrated will improve our understanding of how humans interpret multimodal emotional meanings in real life interactions.

Abstract

Language acquisition involves learning nonadjacent dependencies that can obtain between words in a sentence. Several artificial grammar learning studies have shown that the ability of adults and children to detect dependencies between A and B in frames AXB is influenced by the amount of variation in the X element. This paper presents a model of statistical learning which displays similar behavior on this task and generalizes in a human-like way. The model was also used to predict human behavior for increased distance and more variation in dependencies. We compare our model-based approach with the standard invariance account of the variability effect.

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

Recent studies suggest that high-frequency words may benefit speech segmentation (Bortfeld, Morgan, Golinkoff, & Rathbun, 2005) and grammatical categorisation (Monaghan, Christiansen, & Chater, 2007). To date, these tasks have been examined separately, but not together. We familiarised adults with continuous speech comprising repetitions of target words, and compared learning to a language in which targets appeared alongside high-frequency marker words. Marker words reliably preceded targets, and distinguished them into two otherwise unidentifiable categories. Participants completed a 2AFC segmentation test, and a similarity judgement categorisation test. We tested transfer to a word-picture mapping task, where words from each category were used either consistently or inconsistently to label actions/objects. Participants segmented the speech successfully, but only demonstrated effective categorisation when speech contained high-frequency marker words. The advantage of marker words extended to the early stages of the transfer task. Findings indicate the same high-frequency words may assist speech segmentation and grammatical categorisation.

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 with Rapid Serial Visual Presentation (RSVP) has shown promise for optimizing screen space and increasing reading speed without compromising comprehension. Given the wide use of small-screen devices, the present study compared RSVP and traditional reading on three types of reading comprehension, reading speed, and subjective measures on a smart watch. Results confirm previous studies that show faster reading speed with RSVP without detracting from comprehension. Subjective data indicate that Traditional is strongly preferred to RSVP as a primary reading method. Given the optimal use of screen space, increased speed and comparable comprehension, future studies should focus on making RSVP a more comfortable format.

Abstract

Not much is known about event apprehension, the earliest stage of information processing in elicited language production studies, using pictorial stimuli. A reason for our lack of knowledge on this process is that apprehension happens very rapidly (<350 ms after stimulus onset, Griffin & Bock 2000), making it difficult to measure the process directly. To broaden our understanding of apprehension, we analyzed landing positions and onset latencies of first fixations on visual stimuli (pictures of real-world events) given short stimulus presentation times, presupposing that the first fixation directly results from information processing during apprehension

Abstract

The present paper considers the problem of annotating bibliographical references with labels/classes, given training data of references already annotated with labels. The problem is an instance of document categorization where the documents are short and written in a wide variety of languages. The skewed distributions of title words and labels calls for special carefulness when choosing a Machine Learning approach. The present paper describes how to induce Disjunctive Normal Form formulae (DNFs), which have several advantages over Decision Trees. The approach is evaluated on a large real-world collection of bibliographical references.

Abstract

This corpus study demonstrates that the realization of wordfinal /t/ in Dutch past-participles in various speech styles is affected by a word’s predictability and paradigmatic relative frequency. In particular, /t/s are shorter and more often absent if the two preceding words are more predictable. In addition, /t/s, especially in irregular verbs, are more reduced, the lower the verb’s lemma frequency relative to the past-participle’s frequency. Both effects are more pronounced in more spontaneous speech. These findings are expected if speech planning plays an important role in speech reduction. Index Terms: pronunciation variation, acoustic reduction, corpus research, word predictability, morphological decomposability

Abstract

Children with developmental language disorder (DLD) regularly use the base form of verbs (e.g., dance) instead of inflected forms (e.g., danced). We propose an account of this behavior in which children with DLD have difficulty processing novel inflected verbs in their input. This leads the inflected form to face stronger competition from alternatives. Competition is resolved by the production of a more accessible alternative with high semantic overlap with the inflected form: in English, the bare form. We test our account computationally by training a nonparametric Bayesian model that infers the productivity of the inflectional suffix (-ed). We systematically vary the number of novel types of inflected verbs in the input to simulate the input as processed by children with and without DLD. Modeling results are consistent with our hypothesis, suggesting that children’s inconsistent use of inflectional morphemes could stem from inferences they make on the basis of impoverished data.

Abstract

Several studies examined cue competition in human learning by testing learners on a combination of conflicting cues rooting for different outcomes, with each cue perfectly predicting its outcome. A common result has been that learners faced with cue conflict choose the outcome associated with the rare cue (the Inverse Base Rate Effect, IBRE). Here, we investigate cue competition including IBRE with sentences containing cues to meanings in a visual world. We do not observe IBRE. Instead we find that position in the sentence strongly influences cue salience. Faced with conflict between an initial cue and a non-initial cue, learners choose the outcome associated with the initial cue, whether frequent or rare. However, a frequent configuration of non-initial cues that are not sufficiently salient on their own can overcome a competing salient initial cue rooting for a different meaning. This provides a possible explanation for certain recurring patterns in language change.

Abstract

We automatically predict properties of
wines on the basis of smell and flavor de-
scriptions from experts’ wine reviews. We
show wine experts are capable of describ-
ing their smell and flavor experiences in
wine reviews in a sufficiently consistent
manner, such that we can use their descrip-
tions to predict properties of a wine based
solely on language. The experimental re-
sults show promising F-scores when using
lexical and semantic information to predict
the color, grape variety, country of origin,
and price of a wine. This demonstrates,
contrary to popular opinion, that wine ex-
perts’ reviews really are informative.

Abstract

Using the visual-word paradigm, the present study investigated the effects of word onset and offset masking on the time course of non-native spoken-word recognition in the presence of background noise. In two experiments, Dutch non-native listeners heard English target words, preceded by carrier sentences that were noise-free (Experiment 1) or contained intermittent noise (Experiment 2). Target words were either onset- or offset-masked or not masked at all. Results showed that onset masking delayed target word recognition more than offset masking did, suggesting that – similar to natives – non-native listeners strongly rely on word onset information during word recognition in noise.

Abstract

During spoken-word recognition, listeners experience phonological competition between multiple word candidates, which increases, relative to optimal listening conditions, when speech is masked by noise. Moreover, listeners activate semantic word knowledge during the word’s unfolding. Here, we replicated the effect of background noise on phonological competition and investigated to which extent noise affects the activation of semantic information in phonological competitors. Participants’ eye movements were recorded when they listened to sentences containing a target word and looked at three types of displays. The displays either contained a picture of the target word, or a picture of a phonological onset competitor, or a picture of a word semantically related to the onset competitor, each along with three unrelated distractors. The analyses revealed that, in noise, fixations to the target and to the phonological onset competitor were delayed and smaller in magnitude compared to the clean listening condition, most likely reflecting enhanced phonological competition. No evidence for the activation of semantic information in the phonological competitors was observed in noise and, surprisingly, also not in the clear. We discuss the implications of the lack of an effect and differences between the present and earlier studies.

Abstract

This study uses a classical referential communication task to
investigate the role of co-speech gestures in the process of
coordination. The study manipulates both the common ground between the interlocutors, as well as the visibility of the gestures they use. The findings show that co-speech gestures are an integral part of the referential utterances speakers
produced with regard to both initial references as well as repeated references, and that the availability of gestures appears to impact on interlocutors’ referential oordination. The results are discussed with regard to past research on
common ground as well as theories of gesture production.

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.