Publications

Abstract

This paper joins studies of linguistic variation (e.g. Labov 1972; Dubois & Horvath 2000) and discourse (e.g. Jaworski & Lawson 2005; Jaworski & Pritchard 2005; Thurlow & Jaworski 2010) that consider the intersection between language and tourism. By examining the language attitudes that tourists hold toward linguistic variability in their host community, we find that attitudes differ by context and with respect to tourists’ travel motivations. We suggest that these results are particularly likely in a context like Edinburgh, Scotland, where linguistic variation has an iconic link to place authenticity. We propose that the joint commodification of ‘intelligibility’ and ‘authenticity’ explains this variability. The results raise questions about how the commodity value of travel motivation and the associated context of language use influence language attitudes.

Abstract

This paper studies the robustness of exemplar effects in word comprehension by means of four long-term priming experiments with lexical decision tasks in Dutch. A prime and target represented the same word type and were presented with the same or different degree of reduction. In Experiment 1, participants heard only a small number of trials, a large proportion of repeated words, and stimuli produced by only one speaker. They recognized targets more quickly if these represented the same degree of reduction as their primes, which forms additional evidence for the exemplar effects reported in the literature. Similar effects were found for two speakers who differ in their pronunciations. In Experiment 2, with a smaller proportion of repeated words and more trials between prime and target, participants recognized targets preceded by primes with the same or a different degree of reduction equally quickly. Also, in Experiments 3 and 4, in which listeners were not exposed to one but two types of pronunciation variation (reduction degree and speaker voice), no exemplar effects arose. We conclude that the role of exemplars in speech comprehension during natural conversations, which typically involve several speakers and few repeated content words, may be smaller than previously assumed.

Abstract

Faced with planning problems related to lexical access, speakers take advantage of a major function of disfluencies: buying time. It is reasonable, then, to expect that the structure of disfluencies sheds light on the mechanisms underlying lexical access. Using data from the Switchboard Corpus, we investigated the effect of semantic competition during lexical access on repetition disfluencies. We hypothesized that the more time the speaker needs to access the following unit, the longer the repetition. We examined the repetitions preceding verbs and nouns and tested predictors influencing the accessibility of these items. Results suggest that speed of lexical access negatively correlates with the length of repetition and that the main determinants of lexical access speed differ for verbs and nouns. Longer disfluencies before verbs appear to be due to significant paradigmatic competition from semantically similar verbs. For nouns, they occur when the noun is relatively unpredictable given the preceding context.

Abstract

Three eye-tracking experiments investigated the impact of the complexity of the visual environment on the likelihood of word-object mapping taking place at phonological, semantic and visual levels of representation during language-mediated visual search. Dutch participants heard spoken target words while looking at four objects embedded in displays of different complexity and indicated the presence or absence of the target object. During filler trials the target objects were present, but during experimental trials they were absent and the display contained various competitor objects. For example, given the target word “beaker”, the display contained a phonological (a beaver, bever), a shape (a bobbin, klos), a semantic (a fork, vork) competitor, and an unrelated distractor (an umbrella, paraplu). When objects were presented in simple four-object displays (Experiment 2), there were clear attentional biases to all three types of competitors replicating earlier research (Huettig and McQueen, 2007). When the objects were embedded in complex scenes including four human-like characters or four meaningless visual shapes (Experiments 1, 3), there were biases in looks to visual and semantic but not to phonological competitors. In both experiments, however, we observed evidence for inhibition in looks to phonological competitors, which suggests that the phonological forms of the objects nevertheless had been retrieved. These findings suggest that phonological word-object mapping is contingent upon the nature of the visual environment and add to a growing body of evidence that the nature of our visual surroundings induces particular modes of processing during language-mediated visual search.

Abstract

Conversation Analysis (CA) is an inductive, micro-analytic, and predominantly qualitative
method for studying human social interactions. This chapter describes and illustrates the basic
methods of CA. We first situate the method by describing its sociological foundations, key areas
of analysis, and particular approach in using naturally occurring data. The bulk of the chapter is
devoted to practical explanations of the typical conversation analytic process for collecting data
and producing an analysis. We analyze a candidate interactional practice – the assessmentimplicative
interrogative – using real data extracts as a demonstration of the method, explicitly
laying out the relevant questions and considerations for every stage of an analysis. The chapter
concludes with some discussion of quantitative approaches to conversational interaction, and
links between CA and psycholinguistic concerns

Abstract

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

Abstract

Recent experimental evidence from cognitive psychology and cognitive neuroscience shows that reading acquisition has non-trivial consequences for cognitive processes other than reading per se. In the present chapter I present evidence from three areas of cognition: phonological processing, prediction in language processing, and visual search. These findings suggest that literacy on cognition influences are far-reaching. This implies that a good understanding of the dramatic impact of literacy acquisition on the human mind is an important prerequisite for successful education policy development and guidance of educational support.

Abstract

This chapter deals with the question of whether there is one syntactic system that is shared by language production and comprehension or whether there are two separate systems. It first discusses arguments in favor of one or the other option and then presents the current evidence on the brain structures involved in sentence processing. The results of meta-analyses of numerous neuroimaging studies suggest that there is one system consisting of functionally distinct cortical regions: the dorsal part of Broca’s area subserving compositional syntactic processing; the ventral part of Broca’s area subserving compositional semantic processing; and the left posterior temporal cortex (Wernicke’s area) subserving the retrieval of lexical syntactic and semantic information. Sentence production, the comprehension of simple and complex sentences, and the parsing of sentences containing grammatical violations differ with respect to the recruitment of these functional components.

Abstract

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

Abstract

The human hard palate shows between-subject variation
that is known to influence articulatory strategies.
In order to link such variation to human speech, we
are conducting a cross-sectional MRI study on multiple
populations. A model based on Bezier curves
using only three parameters was fitted to hard palate
MRI tracings using evolutionary computation. The
fits produced consistently yield high accuracies. For
future research, this new method may be used to classify
our MRI data on ethnic origins using e.g., cluster
analyses. Furthermore, we may integrate our model
into three-dimensional representations of the vocal
tract in order to investigate its effect on acoustics and
cultural transmission.

Abstract

Computer models of cultural evolution have shown language properties emerging on interacting agents with a brain that lacks dedicated, nativist language modules. Notably, models using Bayesian agents provide a precise specification of (extra-)liguististic factors (e.g., genetic) that shape language through iterated learning (biases on language), and demonstrate that weak biases get expressed more strongly over time (bias amplification). Other models attempt to lessen assumption on agents’ innate predispositions even more, and emphasize self-organization within agents, highlighting glossogenesis (the development of language from a nonlinguistic state). Ultimately however, one also has to recognize that biology and culture are strongly interacting, forming a coevolving system. As such, computer models show that agents might (biologically) evolve to a state predisposed to language adaptability, where (culturally) stable language features might get assimilated into the genome via Baldwinian niche construction. In summary, while many questions about language evolution remain unanswered, it is clear that it is not to be completely understood from a purely biological, cognitivist perspective. Language should be regarded as (partially) emerging on the social interactions between large populations of speakers. In this context, agent models provide a sound approach to investigate the complex dynamics of genetic biasing on language and speech

Abstract

The idea that presupposition triggers have different intrinsic properties has gradually made its way into the literature on presuppositions and become a current assumption in most approaches. The distinctions mentioned in the different works have been based on introspective data, which seem, indeed, very suggestive. In this paper, we take a different look at some of these distinctions by using a simple experimental approach based on judgment of naturalness about sentences in various contexts. We show that the alleged difference between weak (or soft) and strong (or hard) triggers is not as clear as one may wish and that the claim that they belong to different lexical classes of triggers is probably much too strong.

Abstract

This study investigates the time-course of information processing in both visual as well as in the auditory speech as used for word identification in face-to-face communication. It extends the limited previous research on this topic and provides a valuable database for future research in audiovisual speech perception. An evaluation of models of speech perception by ear and eye in their ability to account for the audiovisual gating data shows a superior role of the fuzzy logical model of perception (FLMP) [1] over additive models of perception. A new dynamic version of the FLMP seems to be a promising model to account for the complex interplay of perceptual and cognitive information in audiovisual spoken word recognition.

Abstract

Mutations of the epidermal growth factor receptor (EGFR) gene are found at a relatively high frequency in glioma, with the most common being the de2-7 EGFR (or EGFRvIII). This mutation arises from an in-frame deletion of exons 2–7, which removes 267 amino acids from the extracellular domain of the receptor. Despite being unable to bind ligand, the de2-7 EGFR is constitutively active at a low level. Transfection of human glioma cells with the de2-7 EGFR has little effect in vitro, but when grown as tumor xenografts this mutated receptor imparts a dramatic growth advantage. We have now mapped the phosphorylation pattern of de2-7 EGFR, both in vivo and in vitro, using a panel of antibodies unique to the different phosphorylated tyrosine residues. Phosphorylation of de2-7 EGFR was detected constitutively at all tyrosine sites surveyed both in vitro and in vivo, including tyrosine 845, a known target in the wild-type EGFR for src kinase. There was a substantial upregulation of phosphorylation at every tyrosine residue of the de2-7 EGFR when cells were grown in vivo compared to the receptor isolated from cells cultured in vitro. Upregulation of phosphorylation could be mimicked in vitro by the addition of specifi c components of the ECM such as collagen via an integrin-dependent mechanism. Since this increase in in vivo phosphorylation enhances de2-7 EGFR signaling, this observation explains why the growth enhancement mediated by de2-7 EGFR is largely restricted to the in vivo environment. In a second set of experiments we analyzed the interaction between EGFRvIII and ErbB2. Co-expression of these proteins in NR6 cells, a mouse fi broblast line devoid of ErbB family members, dramatically enhanced in vivo tumorigenicity of these cells compared to cells expressing either protein alone. Detailed analysis of these xenografts demonstrated that EGFRvIII could heterodimerize and transphosphorylate the ErbB2. Since both EGFRvIII and ErbB2 are commonly expressed at gliomas, this data suggests that the co-expression of these two proteins may enhance glioma tumorigenicity.

Abstract

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

Abstract

The previous literature has suggested that the hand movement in co-speech gestures and signs consists of a series of phases with qualitatively different dynamic characteristics. In this paper, we propose a syntagmatic rule system for movement phases that applies to both co-speech gestures and signs. Descriptive criteria for the rule system were developed for the analysis video-recorded continuous production of signs and gesture. It involves segmenting a stream of body movement into phases and identifying different phase types. Two human coders used the criteria to analyze signs and cospeech gestures that are produced in natural discourse. It was found that the criteria yielded good inter-coder reliability. These criteria can be used for the technology of automatic recognition of signs and co-speech gestures in order to segment continuous production and identify the potentially meaningbearing phase.

Abstract

Unter allen Disziplinen, die sich mit der Erforschung der Sprache befassen, ist die Lexikografie die älteste und die für die Allgemeinheit wichtigste. Die ältesten, noch sehr einfachen Wörterbücher finden sich auf 4000 Jahre alten Tontafeln, und wenn sich heute in einem Haushalt überhaupt ein Buch findet, dann ist es wahrscheinlich ein Wörterbuch. In den letzten zwanzig Jahren ist die kommerzielle wie die von öffentlich finanzierten Forschungsstätten betriebene Lexikografie jedoch in einer ernsthafte Krise geraten. Die großen Wörterbuchverlage haben die Arbeit an umfassenden Wörterbüchern weitestgehend eingestellt, weil sie kaum noch gekauft werden; die Akademien geraten mit ihren Langzeitvorhaben in massive Zeit- und Finanzprobleme. Wenn wir nicht auf die umfassende Beschreibung des deutschen Wortschatzes in all einer Vielfalt und seiner geschichtlichen Entwicklung verzichten wollen, müssen ganz neue Wege gegangen werden: Wörterbücher im traditionellen Sinne müssen durch digitale lexikalische Systeme ersetzt werden, die das vorhandene lexikalische Wissen integrieren, es schrittweise systematisch ausbauen, eigene Recherchen in verlässlichen Corpora ermöglichen und von jedermann frei über das Internet nutzbar sind.

Abstract

This study investigates the effects of adult age and speaker abilities on articulatory precision for sibilant productions. Normal-hearing young adults with
better sibilant discrimination have been shown to produce greater spectral sibilant contrasts. As reduced auditory feedback may gradually impact on feedforward
commands, we investigate whether articulatory precision as indexed by spectral mean for [s] and [S] decreases with age, and more particularly with agerelated
hearing loss. Younger, middle-aged and older adults read aloud words starting with the sibilants [s] or [S]. Possible effects of cognitive, perceptual, linguistic and sociolinguistic background variables
on the sibilants’ acoustics were also investigated. Sibilant contrasts were less pronounced for male than female speakers. Most importantly, for the fricative
[s], the spectral mean was modulated by individual high-frequency hearing loss, but not age. These results underscore that even mild hearing loss already affects articulatory precision.

Abstract

This paper examines the language-specific aspect of the TIME PASSING IS MOTION metaphor and suggests that the temporal construal of time can be influenced by a person's second language. Ahrens and Huang (2002) have analyzed the source domain of MOTION for the TIME metaphor into two special cases. In the special case one, TIME PASSING is an object that moves towards an ego. For example, qimuokao kuai dao le "the final exam is approaching." In the special case two, TIME PASSING is a point (that a plural ego is attached to) that moves across a landscape. For example, women kuai dao qimuokao le "we are approaching the final exam." In addition, in English, the ego in the special case one faces the future while in Chinese, the ego faces the past. The current experiment hypothesizes that English influences the choice of the orientation of the ego in native Chinese speakers who speak English as the second language. 54 subjects are asked to switch the clock time one hour forward. Results show that native Chinese speakers living in the Chinese speaking country tend to move the clock one hour forward to the past (92%) while native Chinese speakers living in an English speaking country are less likely to do so (60%). This implies that the experience of English influences the conceptualization of time in Mandarin Chinese.

Abstract

Speakers of English habitually encode motion events using manner-of-motion verbs (e.g., spin, roll, slide) whereas Spanish speakers rely on path-of-motion verbs (e.g., enter, exit, approach). Here, we ask whether the language-specific verb representations used in encoding motion events induce different modes of “thinking-for-speaking” in Spanish–English bilinguals. That is, assuming that the verb encodes the most salient information in the clause, do bilinguals find the path of motion to be more salient than manner of motion if they had previously described the motion event using Spanish versus English? In our study, Spanish–English bilinguals described a set of target motion events in either English or Spanish and then participated in a nonlinguistic similarity judgment task in which they viewed the target motion events individually (e.g., a ball rolling into a cave) followed by two variants a “same-path” variant such as a ball sliding into a cave or a “same-manner” variant such as a ball rolling away from a cave). Participants had to select one of the two variants that they judged to be more similar to the target event: The event that shared the same path of motion as the target versus the one that shared the same manner of motion. Our findings show that bilingual speakers were more likely to classify two motion events as being similar if they shared the same path of motion and if they had previously described the target motion events in Spanish versus in English. Our study provides further evidence for the “thinking-for-speaking” hypothesis by demonstrating that bilingual speakers can flexibly shift between language-specific construals of the same event “on-the-fly.”

Abstract

Citations play a crucial role in the scientific discourse, in information retrieval, and in bibliometrics. Many initiatives are currently promoting the idea of having free and open citation data. Creation of citation data, however, is not part of the cataloging workflow in libraries nowadays.
In this paper, we present our project Linked Open Citation Database, in which we design distributed processes and a system infrastructure based on linked data technology. The goal is to show that efficiently cataloging citations in libraries using a semi-automatic approach is possible. We specifically describe the current state of the workflow and its implementation. We show that we could significantly improve the automatic reference extraction that is crucial for the subsequent data curation. We further give insights on the curation and linking process and provide evaluation results that not only direct the further development of the project, but also allow us to discuss its overall feasibility.

Abstract

It is widely held that smells and flavors are impossible to put into words. In this paper we test this claim by seeking predictive patterns in wine reviews, which ostensibly aim to provide guides to perceptual content. Wine reviews have previously been critiqued as random and meaningless. We collected an English corpus of wine reviews with their structured metadata, and applied machine learning techniques to automatically predict the wine's color, grape variety, and country of origin. To train the three supervised classifiers, three different information sources were incorporated: lexical bag-of-words features, domain-specific terminology features, and semantic word embedding features. In addition, using regression analysis we investigated basic review properties, i.e., review length, average word length, and their relationship to the scalar values of price and review score. Our results show that wine experts do share a common vocabulary to describe wines and they use this in a consistent way, which makes it possible to automatically predict wine characteristics based on the review text alone. This means that odors and flavors may be more expressible in language than typically acknowledged.

Abstract

Different linguistic modalities (speech or sign) offer different levels at which signals can iconically represent the world. One hypothesis argues that this iconicity has an effect on how linguistic structure emerges. However, exactly how and why these effects might come about is in need of empirical investigation. In this contribution, we present a signal creation experiment in which both the signalling space and the meaning space are manipulated so that different levels and types of iconicity are available between the signals and meanings. Signals are produced using an infrared sensor that detects the hand position of participants to generate auditory feedback. We find evidence that iconicity may be maladaptive for the discrimination of created signals. Further, we implemented Hidden Markov Models to characterise the structure within signals, which was also used to inform a metric for iconicity.

Abstract

We present the Narrative Brain Dataset, an fMRI dataset that was collected during spoken presentation of short excerpts of three
stories in Dutch. Together with the brain imaging data, the dataset contains the written versions of the stimulation texts. The texts are
accompanied with stochastic (perplexity and entropy) and semantic computational linguistic measures. The richness and unconstrained
nature of the data allows the study of language processing in the brain in a more naturalistic setting than is common for fMRI studies.
We hope that by making NBD available we serve the double purpose of providing useful neural data to researchers interested in natural
language processing in the brain and to further stimulate data sharing in the field of neuroscience of language.

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

The lexicon is central to the concerns of disparate disciplines and has correspondingly elicited conflicting proposals about some of its foundational properties. Some suppose that word meanings and their associated concepts are largely universal, while others note that local cultural interests infiltrate every category in the lexicon. This chapter reviews research in two semantic domains—perception and the body—in order to illustrate crosslinguistic similarities and differences in semantic fields. Data is considered from a wide array of languages, especially those from small-scale indigenous communities which are often overlooked. In every lexical field we find considerable variation across cultures, raising the question of where this variation comes from. Is it the result of different ecological or environmental niches, cultural practices, or accidents of historical pasts? Current evidence suggests that diverse pressures differentially shape lexical fields.

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

Concepts are so fundamental to human cognition that Fodor declared the heart of a cognitive science to be its theory of concepts. To study concepts, though, cognitive scientists need to be able to identify some. The prevailing assumption has been that they are revealed by words such as triangle, table, and robin. But languages vary dramatically in how they carve up the world with names. Either ordinary concepts must be heavily language dependent, or names cannot be a direct route to concepts. We asked speakers of English, Dutch, Spanish, and Japanese to name a set of 36 video clips of human locomotion and to judge the similarities among them. We investigated what name inventories, name extensions, scaling solutions on name similarity, and scaling solutions on nonlinguistic similarity from the groups, individually and together, suggest about the underlying concepts. Aggregated naming data and similarity solutions converged on results distinct from individual languages.

Abstract

Words are fundamental to reading and yet over a century of research has not masked the controversies around how words are recognized. We review some old and new research that disproves simple ideas such as words are read as wholes or are simply mapped directly to spoken language. We also review theory and research relevant to the question of sublexical influences in word recognition. We describe orthography and phonology, how they are related to each other and describe a series of new experiments on how these sources of information are processed. Tasks include lexical decision, perceptual identification, and naming. Dependent measures are reaction time, accuracy of performance, and a new measure, initial phoneme duration, that refers to the duration of the first phoneme when the target word is pronounced. Important factors in resolving the controversies include the realization that reading has multiple determinants, as well as evaluating the type of task, proper controls such as familiarity of the test items and accuracy of measurement of the response. We also address potential limitations with measures related to the mapping between orthography and phonology, and show that the existence of a sound-to-spelling consistency effect does not require interactive activation, but can be explained and predicted by a feedforward model, the Fuzzy logical model of perception.

Abstract

Information structure is a subfield of linguistic research dealing with the ways speakers encode instructions to the hearer on how to process the message relative to their temporary mental states. To this end, sentences are segmented into parts conveying known and yet-unknown information, usually labeled ‘topic’ and ‘focus.’ Many languages have developed specialized grammatical and lexical means of indicating this segmentation.

Abstract

The results of a word-spotting experiment are presented in which Dutch listeners tried to spot different types of bisyllabic Dutch words embedded in different types of nonsense contexts. Embedded verbs were not reliably harder to spot than embedded nouns; this suggests that nouns and verbs are recognised via the same basic processes. Iambic words were no harder to spot than trochaic words, suggesting that trochaic words are not in principle easier to recognise than iambic words. Words were harder to spot in consonantal contexts (i.e., contexts which themselves could not be words) than in longer contexts which contained at least one vowel (i.e., contexts which, though not words, were possible words of Dutch). A control experiment showed that this difference was not due to acoustic differences between the words in each context. The results support the claim that spoken-word recognition is sensitive to the viability of sound sequences as possible words.

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

Frequent and predictable words are generally pronounced with less effort and are therefore acoustically more reduced than less frequent or unpredictable words. Local predictability can be operationalised by Transitional Probability (TP), which indicates how likely a word is to occur given its immediate context. We investigated whether and how probabilistic reduction effects on word durations change with adult age when reading aloud content words embedded in sentences. The results showed equally large frequency effects on verb and noun durations for both younger (Mage = 20 years) and older (Mage = 68 years) adults. Backward TP also affected word duration for younger and older adults alike. ForwardTP, however, had no significant effect on word duration in either age group. Our results resemble earlier findings of more robust BackwardTP effects compared to ForwardTP effects. Furthermore, unlike often reported decline in predictive processing with aging, probabilistic reduction effects remain stable across adulthood.