Publications

Abstract

Linguistic traits are often seen as reflecting cognitive biases and constraints (e.g. Christiansen & Chater, 2008). However, language must also adapt to properties of the channel through which communication between individuals occurs. Perhaps the most basic aspect of any communication channel is noise. Communicative signals can be blocked, degraded or distorted by other sources in the environment. This poses a fundamental problem for communication. On average, channel disruption accompanies problems in conversation every 3 minutes (27% of cases of other-initiated repair, Dingemanse et al., 2015). Linguistic signals must adapt to this harsh environment. While modern language structures are robust to noise (e.g. Piantadosi et al., 2011), we investigate how noise might have shaped the early emergence of structure in language. The obvious adaptation to noise is redundancy. Signals which are maximally different from competitors are harder to render ambiguous by noise. Redundancy can be increased by adding differentiating segments to each signal (increasing the diversity of segments). However, this makes each signal more complex and harder to learn. Under this strategy, holistic languages may emerge. Another strategy is reduplication - repeating parts of the signal so that noise is less likely to disrupt all of the crucial information. This strategy does not increase the difficulty of learning the language - there is only one extra rule which applies to all signals. Therefore, under pressures for learnability, expressivity and redundancy, reduplicated signals are expected to emerge. However, reduplication is not a pervasive feature of words (though it does occur in limited domains like plurals or iconic meanings). We suggest that this is due to the pressure for redundancy being lifted by conversational infrastructure for repair. Receivers can request that senders repeat signals only after a problem occurs. That is, robustness is achieved by repeating the signal across conversational turns (when needed) instead of within single utterances. As a proof of concept, we ran two iterated learning chains with pairs of individuals in generations learning and using an artificial language (e.g. Kirby et al., 2015). The meaning space was a structured collection of unfamiliar images (3 shapes x 2 textures x 2 outline types). The initial language for each chain was the same written, unstructured, fully expressive language. Signals produced in each generation formed the training language for the next generation. Within each generation, pairs played an interactive communication game. The director was given a target meaning to describe, and typed a word for the matcher, who guessed the target meaning from a set. With a 50% probability, a contiguous section of 3-5 characters in the typed word was replaced by ‘noise’ characters (#). In one chain, the matcher could initiate repair by requesting that the director type and send another signal. Parallel generations across chains were matched for the number of signals sent (if repair was initiated for a meaning, then it was presented twice in the parallel generation where repair was not possible) and noise (a signal for a given meaning which was affected by noise in one generation was affected by the same amount of noise in the parallel generation). For the final set of signals produced in each generation we measured the signal redundancy (the zip compressibility of the signals), the character diversity (entropy of the characters of the signals) and systematic structure (z-score of the correlation between signal edit distance and meaning hamming distance). In the condition without repair, redundancy increased with each generation (r=0.97, p=0.01), and the character diversity decreased (r=-0.99,p=0.001) which is consistent with reduplication, as shown below (part of the initial and the final language): Linear regressions revealed that generations with repair had higher overall systematic structure (main effect of condition, t = 2.5, p < 0.05), increasing character diversity (interaction between condition and generation, t = 3.9, p = 0.01) and redundancy increased at a slower rate (interaction between condition and generation, t = -2.5, p < 0.05). That is, the ability to repair counteracts the pressure from noise, and facilitates the emergence of compositional structure. Therefore, just as systems to repair damage to DNA replication are vital for the evolution of biological species (O’Brien, 2006), conversational repair may regulate replication of linguistic forms in the cultural evolution of language. Future studies should further investigate how evolving linguistic structure is shaped by interaction pressures, drawing on experimental methods and naturalistic studies of emerging languages, both spoken (e.g Botha, 2006; Roberge, 2008) and signed (e.g Senghas, Kita, & Ozyurek, 2004; Sandler et al., 2005).

Abstract

For (semi-)automated subject indexing systems in digital libraries, it is often more practical to use metadata such as the title of a publication instead of the full-text or the abstract. Therefore, it is desirable to have good text mining and text classification algorithms that operate well already on the title of a publication. So far, the classification performance on titles is not competitive with the performance on the full-texts if the same number of training samples is used for training. However, it is much easier to obtain title data in large quantities and to use it for training than full-text data. In this paper, we investigate the question how models obtained from training on increasing amounts of title training data compare to models from training on a constant number of full-texts. We evaluate this question on a large-scale dataset from the medical domain (PubMed) and from economics (EconBiz). In these datasets, the titles and annotations of millions of publications are available, and they outnumber the available full-texts by a factor of 20 and 15, respectively. To exploit these large amounts of data to their full potential, we develop three strong deep learning classifiers and evaluate their performance on the two datasets. The results are promising. On the EconBiz dataset, all three classifiers outperform their full-text counterparts by a large margin. The best title-based classifier outperforms the best full-text method by 9.4%. On the PubMed dataset, the best title-based method almost reaches the performance of the best full-text classifier, with a difference of only 2.9%.

Abstract

There are three main strands of research which have investigated people’s intuitive knowledge of objects in motion. (1) Knowledge of the trajectories of objects in motion; (2) knowledge of the causes of motion; and (3) the categorisation of motion as to whether it has been produced by something animate or inanimate. We provide a brief introduction to each of these areas. We then point to some linguistic and cultural differences which may have consequences for people’s knowledge of objects in motion. Finally, we describe two experimental tasks and an ethnographic task that will allow us to collect data in order to establish whether, indeed, there are interesting cross-linguistic/cross-cultural differences in lay theories of objects in motion.

Abstract

What is the relationship between the language we speak and the way we think? Researchers working at the interface of language and cognition hope to understand the complex interplay between linguistic structures and the way the mind works. This is thorny territory in anthropology and its closely allied disciplines, such as linguistics and psychology.

Abstract

Lexical knowledge influences how human listeners make decisions about speech sounds. Positive lexical effects (faster responses to target sounds in words than in nonwords) are robust across several laboratory tasks, while negative effects (slower responses to targets in more word-like nonwords than in less word-like nonwords) have been found in phonetic decision tasks but not phoneme monitoring tasks. The present experiments tested whether negative lexical effects are therefore a task-specific consequence of the forced choice required in phonetic decision. We compared phoneme monitoring and phonetic decision performance using the same Dutch materials in each task. In both experiments there were positive lexical effects, but no negative lexical effects. We observe that in all studies showing negative lexical effects, the materials were made by cross-splicing, which meant that they contained perceptual evidence supporting the lexically-consistent phonemes. Lexical knowledge seems to influence phonemic decision-making only when there is evidence for the lexically-consistent phoneme in the speech signal.

Abstract

We briefly describe the Merge model of phonemic decision-making, and, in the light of general arguments about the possible role of feedback in spoken-word recognition, defend Merge's feedforward structure. Merge not only accounts adequately for the data, without invoking feedback connections, but does so in a parsimonious manner.

Abstract

The ultimate goal of our research is to improve an existing speech-based computational model of human speech recognition on the task of simulating the role of fine-grained phonetic information in human speech processing. As part of this work we are investigating articulatory feature classifiers that are able to create reliable and accurate transcriptions of the articulatory behaviour encoded in the acoustic speech signal. Articulatory feature (AF) modelling of speech has received a considerable amount of attention in automatic speech recognition research. Different approaches have been used to build AF classifiers, most notably multi-layer perceptrons. Recently, deep neural networks have been applied to the task of AF classification. This paper aims to improve AF classification by investigating two different approaches: 1) investigating the usefulness of a deep Convolutional neural network (CNN) for AF classification; 2) integrating the Mel filtering operation into the CNN architecture. The results showed a remarkable improvement in classification accuracy of the CNNs over state-of-the-art AF classification results for Dutch, most notably in the minority classes. Integrating the Mel filtering operation into the CNN architecture did not further improve classification performance.

Abstract

This study demonstrates how interaction – specifically negotiation and repair – facilitates the emergence, evolution, and conventionalization of a silent gesture communication system. In a modified iterated learning paradigm, partners communicated noun-verb meanings using only silent gesture. The need to disambiguate similar noun-verb pairs drove these "new" language users to develop a morphology that allowed for quicker processing, easier transmission, and improved accuracy. The specific morphological system that emerged came about through a process of negotiation within the dyad, namely by means of repair. By applying a discourse analytic approach to the use of repair in an experimental methodology for language evolution, we are able to determine not only if interaction facilitates the emergence and learnability of a new communication system, but also how interaction affects such a system

Abstract

Analyzing EEG signals recorded while participants are listening to continuous speech with the purpose of testing linguistic hypotheses is complicated by the fact that the signals simultaneously reflect exogenous acoustic excitation and endogenous linguistic processing. This makes it difficult to trace subtle differences that occur in mid-sentence position. We apply an analysis based on multivariate temporal response functions to uncover subtle mid-sentence effects. This approach is based on a per-stimulus estimate of the response of the neural system to speech input. Analyzing EEG signals predicted on the basis of the response functions might then bring to light conditionspecific differences in the filtered signals. We validate this approach by means of an analysis of EEG signals recorded with isolated word stimuli. Then, we apply the validated method to the analysis of the responses to the same words in the middle of meaningful sentences.

Abstract

This paper reports the results of a study on the prosodic marking of broad and contrastive focus in three language varieties of which two are in contact: bilingual Peruvian Spanish, Quechua and Peninsular Spanish. An interactive communicative task revealed that the prosodic marking of contrastive focus was limited in all three language varieties. No systematic correspondence was observed between specific contour/accent types and focus, and the phonetic marking of contrastive focus was weak and restricted to phrase-final position. Interestingly, we identified two contours for bilingual Peruvian Spanish that were present in Quechua, but not in Peninsular Spanish, providing evidence for a prosodic transfer from Quechua to Spanish in Quechua-Spanish bilinguals.

Abstract

Can studying left- and right-handers inform us about cognition? In this chapter, we give an overview of research showing that studying left- and right-handers is informative for understanding the way the brain is organized (i.e., lateralized), as there appear to be differences between left- and right-handers in this respect, but also on the behavioral level handedness studies can provide new insights. According to theories of embodied cognition, our body can influence cognition. Given that left- and right-handers use their bodies differently, this might reflect their performance on an array of cognitive tasks. Indeed, handedness can have an influence on, for instance, what side of space we judge as more positive, the way we gesture, how we remember things, and how we learn new words. Laterality research can, therefore, provide valuable information as to how we act and why

Abstract

Egophoric verbal marking is a typological feature common to Barbacoan languages, but otherwise unknown in the Andean sphere. The verbal systems of three out of the four living Barbacoan languages, Cha’palaa, Tsafiki and Awa Pit, have previously been shown to express egophoric contrasts. The status of Guambiano has, however, remained uncertain. In this chapter, I show that there are in fact two layers of egophoric or egophoric-like marking visible in Guambiano’s grammar. Guambiano patterns with certain other (non-Barbacoan) languages in having ego-categories which function within a broader evidential system. It is additionally possible to detect what is possibly a more archaic layer of egophoric marking in Guambiano’s verbal system. This marking may be inherited from a common Barbacoan system, thus pointing to a potential genealogical basis for the egophoric patterning common to these languages. The multiple formal expressions of egophoricity apparent both within and across the four languages reveal how egophoric contrasts are susceptible to structural renewal, suggesting a pan-Barbacoan preoccupation with the linguistic encoding of self-knowledge.

Abstract

Two word-spotting experiments are reported that examine whether the Possible-Word Constraint (PWC) [1] is a language-specific or language-universal strategy for the segmentation of continuous speech. The PWC disfavours parses which leave an impossible residue between the end of a candidate word and a known boundary. The experiments examined cases where the residue was either a CV syllable with a lax vowel, or a CVC syllable with a schwa. Although neither syllable context is a possible word in English, word-spotting in both contexts was easier than with a context consisting of a single consonant. The PWC appears to be language-universal rather than language-specific.

Abstract

Simulations explored the inability of the TRACE model of spoken-word recognition to model the effects on human listening of subcategorical mismatch in word forms. The source of TRACE's failure lay not in interactive connectivity, not in the presence of inter-word competition, and not in the use of phonemic representations, but in the need for continuously optimised interpretation of the input. When an analogue of TRACE was allowed to cycle to asymptote on every slice of input, an acceptable simulation of the subcategorical mismatch data was achieved. Even then, however, the simulation was not as close as that produced by the Merge model, which has inter-word competition, phonemic representations and continuous optimisation (but no interactive connectivity).

Abstract

There is a long-standing assumption that gestural forms are geared by a set of modes of representation (acting, representing, drawing, moulding) with each technique expressing speakers’ focus of attention on specific aspects of referents (Müller, 2013). Beyond different taxonomies describing the modes of representation, it remains unclear what factors motivate certain depicting techniques over others. Results from a pantomime generation task show that pantomimes are not entirely idiosyncratic but rather follow generalisable patterns constrained by their semantic category. We show that a) specific modes of representations are preferred for certain objects (acting for manipulable objects and drawing for non-manipulable objects); and b) that use and ordering of deictics and modes of representation operate in tandem to distinguish between semantically related concepts (e.g., “to drink” vs “mug”). This study provides yet more evidence that our ability to communicate through silent gesture reveals systematic ways to describe events and objects around us

Abstract

A database is presented of relative familiarity ratings for 24 sets of Japanese words, each set comprising words overlapping in the initial portions. These ratings are useful for the generation of material sets for research in the recognition of spoken words.

Abstract

In this paper we describe a general scheme for internationalization of our talking head, Baldi, to speak other languages. We describe the modular structure of the auditory/visual synthesis software. As an example, we have created a synthetic Arabic talker, which is evaluated using a noisy word recognition task comparing this talker with a natural one.

Abstract

Our ability to use language is multimodal and requires tight coordination between what is expressed in speech and in gesture, such as pointing or iconic gestures that convey semantic, syntactic and pragmatic information related to speakers’ messages. Interestingly, what is expressed in gesture and how it is coordinated with speech differs in speakers of different languages. This paper discusses recent findings on the development of children’s multimodal expressions taking cross-linguistic variation into account. Although some aspects of speech-gesture development show language-specificity from an early age, it might still take children until nine years of age to exhibit fully adult patterns of cross-linguistic variation. These findings reveal insights about how children coordinate different levels of representations given that their development is constrained by patterns that are specific to their languages.

Abstract

Use of language in face-to-face context is multimodal. Production and perception of speech take place in the context of visual articulators such as lips, face, or hand gestures which convey relevant information to what is expressed in speech at different levels of language. While lips convey information at the phonological level, gestures contribute to semantic, pragmatic, and syntactic information, as well as to discourse cohesion. This chapter overviews recent findings showing that speech and gesture (e.g. a drinking gesture as someone says, “Would you like a drink?”) interact during production and comprehension of language at the behavioral, cognitive, and neural levels. Implications of these findings for current psycholinguistic theories and how they can be expanded to consider the multimodal context of language processing are discussed.

Abstract

Iconicity is a fundamental feature of human language. However its processing consequences at the behavioral and neural level in spoken word comprehension are not well understood. The current paper presents the behavioral and electrophysiological outcome of an auditory lexical decision task in which native speakers of Dutch listened to onomatopoeic words and matched control words while their electroencephalogram was recorded. Behaviorally, onomatopoeic words were processed as quickly and accurately as words with an arbitrary mapping between form and meaning. Event-related potentials time-locked to word onset revealed a significant decrease in negative amplitude in the N2 and N400 components and a late positivity for onomatopoeic words in comparison to the control words. These findings advance our understanding of the temporal dynamics of iconic form-meaning mapping in spoken word comprehension and suggest interplay between the neural representations of real-world sounds and spoken words.

Abstract

Gender-(mis)matching pronouns have been studied extensively in experiments. However, a phenomenon common to various languages has thus far been overlooked: the systemic use of non-feminine pronouns when referring to female individuals. The present study is the first to provide experimental insights into the interpretation of such a pronoun: Limburgian zien ‘his/its’ and Dutch zijn ‘his/its’ are grammatically ambiguous between masculine and neuter, but while Limburgian zien can refer to women, the Dutch equivalent zijn cannot. Employing an acceptability judgment task, we presented speakers of Limburgian (N = 51) with recordings of sentences in Limburgian featuring zien, and speakers of Dutch (N = 52) with Dutch translations of these sentences featuring zijn. All sentences featured a potential male or female antecedent embedded in a stereotypically male or female context. We found that ratings were higher for sentences in which the pronoun could refer back to the antecedent. For Limburgians, this extended to sentences mentioning female individuals. Context further modulated sentence appreciation. Possible mechanisms regarding the interpretation of zien as coreferential with a female individual will be discussed.

Abstract

Word count estimation (WCE) from audio recordings has a number of applications, including quantifying the amount of speech that language-learning infants hear in their natural environments, as captured by daylong recordings made with devices worn by infants. To be applicable in a wide range of scenarios and also low-resource domains, WCE tools should be extremely robust against varying signal conditions and require minimal access to labeled training data in the target domain. For this purpose, earlier work has used automatic syllabification of speech, followed by a least-squares-mapping of syllables to word counts. This paper compares a number of previously proposed syllabifiers in the WCE task, including a supervised bi-directional long short-term memory (BLSTM) network that is trained on a language for which high quality syllable annotations are available (a “high resource language”), and reports how the alternative methods compare on different languages and signal conditions. We also explore additive noise and varying-channel data augmentation strategies for BLSTM training, and show how they improve performance in both matching and mismatching languages. Intriguingly, we also find that even though the BLSTM works on languages beyond its training data, the unsupervised algorithms can still outperform it in challenging signal conditions on novel languages.

Abstract

Infants, children and adults are capable of implicitly extracting regularities from their environment through statistical learning (SL). SL is present from early infancy and found across tasks and modalities, raising questions about the domain generality of SL. However, little is known about its’ developmental trajectory: Is SL fully developed capacity in infancy, or does it improve with age, like other cognitive skills? While SL is well established in infants and adults, only few studies have looked at SL across development with conflicting results: some find age-related improvements while others do not. Importantly, despite its postulated role in language learning, no study has examined the developmental trajectory of auditory SL throughout childhood. Here, we conduct a large-scale study of children's auditory SL across a wide age-range (5-12y, N=115). Results show that auditory SL does not change much across development. We discuss implications for modality-based differences in SL and for its role in language acquisition.

Abstract

Recent work suggests that cultural transmission can lead to the emergence of linguistic structure as speakers’ weak individual biases become amplified through iterated learning. However, to date, no published study has demonstrated a similar emergence of linguistic structure in children. This gap is problematic given that languages are mainly learned by children and that adults may bring existing linguistic biases to the task. Here, we conduct a large-scale study of iterated language learning in both children and adults, using a novel, child-friendly paradigm. The results show that while children make more mistakes overall, their languages become more learnable and show learnability biases similar to those of adults. Child languages did not show a significant increase in linguistic structure over time, but consistent mappings between meanings and signals did emerge on many occasions, as found with adults. This provides the first demonstration that cultural transmission affects the languages children and adults produce similarly.

Abstract

The question of whether intonation events have a categorical mental representation has long been a puzzle in prosodic research, and one that experiments testing production and perception across category boundaries have failed to definitively resolve. This paper takes the alternative approach of looking for evidence of structure within a postulated category by testing for a Perceptual Magnet Effect (PME). PME has been found in boundary tones but has not previously been conclusively found in pitch accents. In this investigation, perceived goodness and discriminability of re-synthesised Dutch nuclear rise contours (L*H H%) were evaluated by naive native speakers of Dutch. The variation between these stimuli was quantified using a polynomial-parametric modelling approach (i.e. the SOCoPaSul model) in place of the traditional approach whereby excursion size, peak alignment and pitch register are used independently of each other to quantify variation between pitch accents. Using this approach to calculate the acoustic-perceptual distance between different stimuli, PME was detected: (1) rated goodness, decreased as acoustic-perceptual distance relative to the prototype increased, and (2) equally spaced items far from the prototype were less frequently generalised than equally spaced items in the neighbourhood of the prototype. These results support the concept of categorically distinct intonation events.

Abstract

Many previous studies have shown that both infants and adults are skilled statistical learners. Because statistical learning is affected by attention, learners' ability to manage their attention can play a large role in what they learn. However, it is still unclear how learners allocate their attention in order to gain information in a visual environment containing multiple objects, especially how prior visual experience (i.e., familiarly of objects) influences where people look. To answer these questions, we collected eye movement data from adults exploring multiple novel objects while manipulating object familiarity with global (frequencies) and local (repetitions) regularities. We found that participants are sensitive to both global and local statistics embedded in their visual environment and they dynamically shift their attention to prioritize some objects over others as they gain knowledge of the objects and their distributions within the task.

Abstract

For almost two decades, the poor performance observed with the so-called Director task has been interpreted as evidence of limited use of Theory of Mind in communication. Here we propose a probabilistic model of common ground in referential communication that derives three inferences from an utterance: what the speaker is talking about in a visual context, what she knows about the context, and what referential expressions she prefers. We tested our model by comparing its inferences with those made by human participants and found that it closely mirrors their judgments, whereas an alternative model compromising the hearer’s expectations of cooperativeness and efficiency reveals a worse fit to the human data. Rather than assuming that common ground is fixed in a given exchange and may or may not constrain reference resolution, we show how common ground can be inferred as part of the process of reference assignment.

Abstract

While there are many studies on information retrieval models using full-text, there are presently no comparison studies of full-text retrieval vs. retrieval only over the titles of documents. On the one hand, the full-text of documents like scientific papers is not always available due to, e.g., copyright policies of academic publishers. On the other hand, conducting a search based on titles alone has strong limitations. Titles are short and therefore may not contain enough information to yield satisfactory search results. In this paper, we compare different retrieval models regarding their search performance on the full-text vs. only titles of documents. We use different datasets, including the three digital library datasets: EconBiz, IREON, and PubMed. The results show that it is possible to build effective title-based retrieval models that provide competitive results comparable to full-text retrieval. The difference between the average evaluation results of the best title-based retrieval models is only 3% less than those of the best full-text-based retrieval models.

Abstract

In the language Duna (Trans New Guinea), egophoric distributional patterns are a pervasive characteristic of verbal morphology, but do not comprise a single coherent system. Many morphemes, including evidential markers and future time inflections, show strong tendencies to co-occur with ‘informant’ subjects (the speaker in a declarative, the addressee in an interrogative), or alternatively with non-informant subjects. The person sensitivity of the Duna forms is observable in frequency, speaker judgments of sayability, and subject implicatures. Egophoric and non-egophoric distributional patterns are motivated by the individual semantics of the morphemes, their perspective-taking properties, and logical and/or conventionalised expectations of how people experience and talk about events. Distributional tendencies can also be flouted, providing a resource for speakers to convey attitudes towards their own knowledge and experiences, or the knowledge and experiences of others.

Abstract

Languages with egophoric systems require their users to pay special attention to who knows what in the speech situation, providing formal marking of whether the speaker or addressee has personal knowledge of the event being discussed. Such systems have only recently come to be studied in cross-linguistic perspective. This chapter has two aims in regard to contributing to our understanding of egophoric marking. Firstly, it presents relevant data from a relatively under-described and endangered language, Kaluli (aka Bosavi), spoken in Papua New Guinea. Unusually, Kaluli tense inflections appear to show a mix of both egophoric and first vs non-first person-marking features, as well as other contrasts that are broadly relevant to a typology of egophoricity, such as special constructions for the expression of involuntary experience. Secondly, the chapter makes a preliminary foray into issues concerning egophoric marking and child language, drawing on a naturalistic corpus of child-caregiver interactions. Questions for future investigation raised by the Kaluli data concern, for example, the potentially challenging nature of mastering inflections that are sensitive to both person and speech act type, the possible role of question-answer pairs in children’s acquisition of egophoric morphology, and whether there are special features of epistemic access and authority that relate particularly to child-adult interactions.

Abstract

Fine-Tracker is a speech-based model of human speech
recognition. While previous work has shown that Fine-Tracker
is successful at modelling aspects of human spoken-word
recognition, its speech recognition performance is not
comparable to that of human performance, possibly due to
suboptimal intermediate articulatory feature (AF)
representations. This study investigates the effect of improved
AF representations, obtained using a state-of-the-art deep
convolutional network, on Fine-Tracker’s simulation and
recognition performance: Although the improved AF quality
resulted in improved speech recognition; it, surprisingly, did
not lead to an improvement in Fine-Tracker’s simulation power.

Abstract

This work focuses on efficient use of the training material by selecting the optimal set of model topologies. We do this by training multiple word models of each word class, based on a subclassification according to a priori knowledge of the training material. We will examine classification criteria with respect to duration of the word, gender of the speaker, position of the word in the utterance, pauses in the vicinity of the word, and combinations of these. Comparative experiments were carried out on a corpus consisting of Dutch spoken connected digit strings and isolated digits, which are recorded in a wide variety of acoustic conditions. The results show, that classification based on gender of the speaker, position of the digit in the string, pauses in the vicinity of the training tokens, and models based on a combination of these criteria perform significantly better than the set with single models per digit.

Abstract

We have recently developed a new model of human speech recognition, based on automatic speech recognition techniques [1]. The present paper has two goals. First, we show that the new model performs well in the recognition of lexically ambiguous input. These demonstrations suggest that the model is able to operate in the same optimal way as human listeners. Second, we discuss how to relate the behaviour of a recogniser, designed to discover the optimum path through a word lattice, to data from human listening experiments. We argue that this requires a metric that combines both path-based and word-based measures of recognition performance. The combined metric varies continuously as the input speech signal unfolds over time.

Abstract

In this paper, we present a novel computational model of human speech recognition – called SpeM – based on the theory underlying Shortlist. We will show that SpeM, in combination with an automatic phone recogniser (APR), is able to simulate the human speech recognition process from the acoustic signal to the ultimate recognition of words. This joint model takes an acoustic speech file as input and calculates the activation flows of candidate words on the basis of the degree of fit of the candidate words with the input. Experiments showed that SpeM outperforms Shortlist on the recognition of ‘real-life’ input. Furthermore, SpeM performs only slightly worse than an off-the-shelf full-blown automatic speech recogniser in which all words are equally probable, while it provides a transparent computationally elegant paradigm for modelling word activations in human word recognition.

Abstract

This chapter describes neurolinguistic aspects of morphology, morphological theory, and especially morphological processing. It briefly mentions the main processing models in the literature and how they deal with morphological issues, i.e. full-listing models (all morphologically related words are listed separately in the lexicon and are processed individually), full-parsing or decompositional models (morphologically related words are not listed in the lexicon but are decomposed into their constituent morphemes, each of which is listed in the lexicon), and hybrid, so-called dual route, models (regular morphologically related words are decomposed, irregular words are listed). The chapter also summarizes some important findings from the literature that bear on neurolinguistic aspects of morphological processing, from both language comprehension and language production, taking into consideration neuropsychological patient studies as well as studies employing neuroimaging methods.

Abstract

This study investigated the encoding of metrical information during speech production in Dutch. In Experiment 1, participants were asked to judge whether bisyllabic picture names had initial or final stress. Results showed significantly faster decision times for initially stressed targets (e.g., LEpel 'spoon') than for targets with final stress (e.g., liBEL 'dragon fly'; capital letters indicate stressed syllables) and revealed that the monitoring latencies are not a function of the picture naming or object recognition latencies to the same pictures. Experiments 2 and 3 replicated the outcome of the first experiment with bi- and trisyllabic picture names. These results demonstrate that metrical information of words is encoded rightward incrementally during phonological encoding in speech production. The results of these experiments are in line with Levelt's model of phonological encoding.

Abstract

The basic idea behind this task is to find out how languages encode basic shape distinctions such as dimensionality, axial geometry, relative size, etc. More specifically, we want to find out (i) which formal means are used cross linguistically to encode basic shape distinctions, and (ii) which are the semantic distinctions that are made in this domain. In languages with many shape-classifiers, these distinctions are encoded (at least partially) in classifiers. In other languages, positional verbs, descriptive modifiers, such as “flat”, “round”, or nouns such as “cube”, “ball”, etc. might be the preferred means. In this context, we also want to investigate what other “grammatical work” shapeencoding expressions possibly do in a given language, e.g. unitization of mass nouns, or anaphoric uses of shape-encoding classifiers, etc. This task further seeks to determine the role of shape-related parameters which underlie the design of objects in the semantics of the system under investigation.

Abstract

This paper describes how the Trobriand Islanders of Papua New Guinea used to construct their big seagoing masawa canoes and how they used to make their sails, what forms of different knowledge and expertise they needed to do this during various stages of the construction processes, how this knowledge was socially distributed, and the social implications of all the joint communal activities that were necessary until a new canoe could be launched. Then it tries to answer the question why the complex distributed knowledge of how to make a masawa has been gradually getting lost in most of the village communities on the Trobriand Islands; and finally it outlines and discusses the implications of this loss for the Trobriand Islanders' culture, for their social construction of reality, and for their indigenous cognitive capacities.

Abstract

This project aims to investigate how speakers of various languages in indigenous cultures verbally reason about moral issues. The ways in which a solution for a moral problem is found, phrased and justified will be taken as the basis for researching reasoning processes that manifest themselves verbally in the speakers’ arguments put forward to solve a number of moral problems which will be presented to them in the form of unfinished story plots or scenarios that ask for a solution. The plots chosen attempt to present common problems in human society and human behaviour. They should function to elicit moral discussion and/or moral arguments in groups of consultants of at least three persons.

Abstract

This entry takes an interdisciplinary approach to linguistic pragmatics. It discusses how the meaning of utterances can only be understood in relation to overall cultural, social, and interpersonal contexts, as well as to culture-specific conventions and the speech events in which they are embedded. The entry discusses core issues of pragmatics such as speech act theory, conversational implicature, deixis, gesture, interaction strategies, ritual communication, phatic communion, linguistic relativity, ethnography of speaking, ethnomethodology, and conversation analysis. It takes a transdisciplinary view of the field, showing that linguistic pragmatics has its predecessors in other disciplines such as philosophy, psychology, ethology, ethnology, and sociology.

Abstract

Bronislaw Malinowski – based on his experience during his field research on the Trobriand Islands – pointed out that language is first and foremost a tool for creating social bonds. It is a mode of behavior and the meaning of an utterance is constituted by its pragmatic function. Malinowski’s ideas finally led to the formation of the subdiscipline “anthropological linguistics”. This paper presents three observations of the Trobrianders’ attitude to their language Kilivila and their language use in social interactions. They illustrate that whoever wants to successfully research the role of language, culture and cognition in social interaction must be on ‘common ground’ with the researched community.

Abstract

As I have already pointed out elsewhere (Senft 2008; 2010; 2014), the Gricean conversational maxims of Quality – “Try to make your contribution one that is true” – and Manner “Be perspicuous”, specifically “Avoid obscurity of expression” and “Avoid ambiguity” (Grice 1967; 1975; 1978) – are not observed by the Trobriand Islanders of Papua New Guinea, neither in forms of their ritualized communication nor in forms and ways of everyday conversation and other ordinary verbal interactions. The speakers of the Austronesian language Kilivila metalinguistically differentiate eight specific non-diatopical registers which I have called “situational-intentional” varieties. One of these varieties is called “biga sopa”. This label can be glossed as “joking or lying speech, indirect speech, speech which is not vouched for”. The biga sopa constitutes the default register of Trobriand discourse and conversation. This contribution to the workshop on philosophy and pragmatics presents the Trobriand Islanders’ indigenous typology of non-diatopical registers, especially elaborating on the concept of sopa, describing its features, discussing its functions and illustrating its use within Trobriand society. It will be shown that the Gricean maxims of quality and manner are irrelevant for and thus not observed by the speakers of Kilivila. On the basis of the presented findings the Gricean maxims and especially Grice’s claim that his theory of conversational implicature is “universal in application” is critically discussed from a general anthropological-linguistic point of view.

Abstract

Three experiments examined whether infants recognise functors in phrases, and whether their representations of functors are phonetically well specified. Eight- and 13- month-old English infants heard monosyllabic lexical words preceded by real functors (e.g., the, his) versus nonsense functors (e.g., kuh); the latter were minimally modified segmentally (but not prosodically) from real functors. Lexical words were constant across conditions; thus recognition of functors would appear as longer listening time to sequences with real functors. Eightmonth- olds' listening times to sequences with real versus nonsense functors did not significantly differ, suggesting that they did not recognise real functors, or functor representations lacked phonetic specification. However, 13-month-olds listened significantly longer to sequences with real functors. Thus, somewhere between 8 and 13 months of age infants learn familiar functors and represent them with segmental detail. We propose that accumulated frequency of functors in input in general passes a critical threshold during this time.