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One limitation of corpus-based research into the epicentre hypothesis is that it only provides information on structural similarity/difference of varieties but not on the role that attitudes may play in the choice of variants in a pluricentric language. In our case study on verb complementation patterns, we use simulation as a complementary methodology. We build an agent-based model for two speaker communities with English as a second language (ESL) which allows for attitudes towards American and British English to affect the choice of verb complementation. This approach enables us to gauge the likely effect that attitudes towards potential epicentres might have on the choice of variants and to predict patterns of variation we should see in language use. We provide preliminary data from the News On the Web corpus to test whether the predictions are, in fact, borne out. only published online, no volume/issue number ispartof: World Englishes vol:41 issue:3 pages:377-399 status: Published online

Hearing loss (HL) in older adults is associated with a decline in performance on cognitive tasks and the risk of developing dementia. However, very few studies have investigated sex-related effects on these associations. A previous study of cognitively healthy older adults showed an association between HL and lower cognitive performance in females only. In the present study, we examined the effects of sex and hearing on cognition in individuals with mild cognitive impairment (MCI). We predicted that females with HL would be more likely to show poorer performance on the cognitive measures compared to females with normal hearing (NH), while cognitive performance in males would not depend on hearing. We further predicted that these auditory-cognitive associations would not depend on test modality, and would thus be observed in females for both auditory and visual tests.Participants were 101 older adults with amnestic MCI (M = 71 years, 45% females) in the Canadian Consortium on Neurodegeneration in Aging (CCNA) COMPASS-ND study. Performance on the Montreal Cognitive Assessment (MoCA), Rey Auditory Verbal Learning (RAVLT), and Brief Visuospatial Memory Test-Revised (BVMT-R) was analyzed to investigate sex-related differences and/or hearing-related differences. Participants were categorized as having NH or HL using two different measures: pure-tone hearing screening results (normal based on a pure-tone threshold25 dB HL at 2000 Hz in the worse ear) and speech-in-noise speech reception thresholds (SRTs; normal-10 dB SNR on the Canadian Digit Triplet Test [CDTT]).Males and female groups did not differ in age, years of education, or other relevant covariates. Yet, females with better hearing on either pure-tone or speech-in-noise measures outperformed their worse hearing counterparts on the MoCA total score. Additionally, females with better hearing were more likely to recall several words on the MoCA delayed recall trial relative to those with worse hearing. Females with NH showed significant correlations between CDTT SRTs and both MoCA and RAVLT scores, while no correlations were observed in males. In contrast, males but not females showed an effect of hearing group on BVMT-R test status.There were sex-specific differences in auditory-cognitive associations in individuals with MCI. These associations were mostly observed in females and on auditory tests. Potential mechanisms and implications are discussed.

Objectives: In this pilot study, we evaluated the use of electrophysiological measures at rest as paradigm-independent predictors of second language (L2) development for the first time in older adult learners. We then assessed EEG correlates of the learning outcome in a language-switching paradigm after the training, which to date has only been done in younger adults and at intermediate to advanced L2 proficiency. Methods: Ten (Swiss) German-speaking adults between 65–74 years of age participated in an intensive 3-week English training for beginners. A resting-state EEG was recorded before the training to predict the ensuing L2 development (Experiment 1). A language-switching ERP experiment was conducted after the training to assess the learning outcome (Experiment 2). Results: All participants improved their L2 skills but differed noticeably in their individual development. Experiment 1 showed that beta1 oscillations at rest (13–14.5 Hz) predicted these individual differences. We interpret resting-state beta1 oscillations as correlates of attentional capacities and semantic working memory that facilitate the extraction and processing of novel forms and meanings from the L2 input. In Experiment 2, we found that language switching from the L2 into the native language (L1) elicited an N400 component, which was reduced in the more advanced learners. Thus, for learners beginning the acquisition of an L2 in third age, language switching appears to become less effortful with increasing proficiency, suggesting that the lexicons of the L1 and L2 become more closely linked. Conclusions: In sum, our findings extend the available evidence of neurological processes in L2 learning from younger to older adults, suggesting that electrophysiological mechanisms are similar across the lifespan.

We study involuntary micro-movements of both eyes, in addition to saccadic macro-movements, as biometric characteristic. We develop a deep convolutional neural network that processes binocular eye-tracking signals and verifies the viewer’s identity. In order to detect presentation attacks, we develop a model in which the movements are a response to a controlled stimulus. The model detects replay attacks by processing both the controlled but randomized stimulus and the ocular response to this stimulus. We acquire eye movement data from 150 participants, with 4 sessions per participant and conduct experiments on this new and legacy data sets with varying tracker precision and sampling rate. We observe that the model detects replay attacks reliably. For identification and identity verification, the model attains substantially lower error rates than prior work. We explore the relationships between training population size, training data volume, types of visual stimuli, number of training and enrollment sessions, interval between enrollment and probe sessions on one hand and the model performance on the other hand.

Different methods to acquire a language can contribute differently to learning success. In the present study we tested the success of L2 stress contrasts acquisition, when ab initio learners were taught or not about the theoretic nature of L2 stress contrasts. In two 4-hour perceptual training methods, French-speaking listeners received either (a) explicit instructions about Spanish stress patterns and perception activities commonly used in L2 pronunciation courses or (b) no explicit instructions and a unique perception activity, a shape/word matching task. Results showed that French-speaking listeners improved their ability to identify and discriminate stress contrasts in Spanish after training. However, there was no significant difference between explicit and non-explicit training nor was there an effect on stress processing under different phonetic variability conditions. This suggests that in L2 stress acquisition, non-explicit training may benefit ab initio learners as much as explicit instruction and activities used in L2 pronunciation courses.

It has been demonstrated that stress, experienced outside of a relationship, can spill into a relationship and cross over during interactions from one partner to the other. However, the mechanism of how stress cross over in real-time between partners is still unknown. To overcome this limitation, we invited 189 couples (N = 378 individuals) for two interactions and stressed either the man, the woman, or both partners between the interactions with a standardized stress-induction procedure. Vocally-encoded emotional arousal (i.e., fundamental frequency, indexed as fo) was extracted from both partners in 25,834 talk turns. Dynamical systems modeling revealed four patterns of dynamic influence prior to stress induction, which started to erode after the stress induction. This demonstrates that the initially unstressed mates become stressed during the behavioral exchange and stress crosses over from the unstressed partner to the stressed mates, interfering with their ability to down-regulate stress.

Speech rhythm varies with age. In this paper, we examined the role of mean and peak syllable intensity variability in age-related rhythmic changes. Si xteen younger adults and 10 older speakers read 60 sentences in Zurich German. Results revealed that peak syllable intensity variability is significantly smaller in older compared to younger adults; there was no such effect for syllable mean intensity. Reduced fluency, changes in the biomechanical properties of articulators controlling the mouth opening cycles, and compensation strategies for subglottal pressure generation were the most plausible reasons for the obtained age-related syllable intensity variability.

Eye movements are known to reflect cognitive processes in reading, and psychological reading research has shown that eye gaze patterns differ between readers with and without dyslexia. In recent years, researchers have attempted to classify readers with dyslexia based on their eye movements using Support Vector Machines (SVMs). However, these approaches (i) are based on highly aggregated features averaged over all words read by a participant, thus disregarding the sequential nature of the eye movements, and (ii) do not consider the linguistic stimulus and its interaction with the reader's eye movements. In the present work, we propose two simple sequence models that process eye movements on the entire stimulus without the need of aggregating features across the sentence. Additionally, we incorporate the linguistic stimulus into the model in two ways -- contextualized word embeddings and manually extracted linguistic features. The models are evaluated on a Mandarin Chinese dataset containing eye movements from children with and without dyslexia. Our results show that (i) even for a logographic script such as Chinese, sequence models are able to classify dyslexia on eye gaze sequences, reaching state-of-the-art performance, and (ii) incorporating the linguistic stimulus does not help to improve classification performance.

It has been shown that multilingual transformer models are able to predict human reading behavior when fine-tuned on small amounts of eye tracking data. As the cumulated prediction results do not provide insights into the linguistic cues that the model acquires to predict reading behavior, we conduct a deeper analysis of the predictions from the perspective of readability. We try to disentangle the three-fold relationship between human eye movements, the capability of language models to predict these eye movement patterns, and sentence-level readability measures for English. We compare a range of model configurations to multiple baselines. We show that the models exhibit difficulties with function words and that pre-training only provides limited advantages for linguistic generalization.

We present a new machine learning benchmark for reading task classification with the goal of advancing EEG and eye-tracking research at the intersection between computational language processing and cognitive neuroscience. The benchmark task consists of a cross-subject classification to distinguish between two reading paradigms: normal reading and task-specific reading. The data for the benchmark is based on the Zurich Cognitive Language Processing Corpus (ZuCo 2.0), which provides simultaneous eye-tracking and EEG signals from natural reading of English sentences. The training dataset is publicly available, and we present a newly recorded hidden testset. We provide multiple solid baseline methods for this task and discuss future improvements. We release our code and provide an easy-to-use interface to evaluate new approaches with an accompanying public leaderboard: www.zuco-benchmark.com., Frontiers in Psychology, 13, ISSN:1664-1078

In this study, we examined whether the convergence in interlocutors’ vowel acoustics leads to decreasing discriminability between interlocutors’ voices. Ten pairs of Grison and Zürich German speakers produced lexical items before and after dialogue interactions with evidence of vowel convergence in post-dialogue productions. In Experiment 1, native and non-native Swiss German listeners discriminated pairs of speakers whose speech was obtained pre- and post-dialogue. Results showed that listeners’ sensitivity (A’) was higher for native than non-native listeners, but comparable for pre- and post-dialogue recordings. The observed negative correlation between voice discrimination and the acoustic distance in formant space was mainly driven by a single speaker pair. In Experiment 2, the speaker recognition performance of an i-vector-based software was compared in pre- and post-dialogue speech. Results revealed no difference in the system performance between the two conditions. The findings suggest that vowel convergence does not compromise voice discriminability under the given experimental conditions.

The alignment between low-frequency activity in the brain and slow acoustic modulations in the speech signal depicts a core principle in present theories of speech perceptionda process referred to as 'neural speech tracking'. While most older adults, particularly those with highly prevalent age-related hearing loss, have difficulties with speech perception and comprehension, the impact of hearing loss on neural speech tracking is still unclear. In this study we investigated the effects of pure-tone hearing loss and different types of background noise on the neural tracking response in a large sample of older adults (N = 101). Furthermore, we examined whether the neural tracking response was predictive for speech comprehension. For this purpose, we obtained scalp EEG from our participants who had varying degrees of pure-tone hearing loss (7.5-59.6 dB HL for .5-8 kHz pure tones) while they listened to sentences in quiet, pink and multi-talker babble noise. Speech tracking was quantified by computing the cross-correlation between the EEG signal and the amplitude envelope of the sentences heard. A higher degree of pure-tone hearing loss was associated with greater neural speech tracking (i.e., greater cross-correlation). Additionally, neural speech tracking showed a positive association with speech comprehension. This relationship was modulated by the degree of pure-tone hearing loss with hearing-impaired participants benefitting more from greater neural speech tracking. Our results highlight the potential of neural speech tracking as an objective measure of speech comprehension and as a possible target mechanism for clinical interventions such as neurofeedback. Furthermore, the interaction between speech tracking and pure-tone hearing loss suggests a compensatory mechanism by which the hearing-impaired rely more on slow amplitude modulations in the speech signal. (C) 2022 The Author(s). Published by Elsevier Ltd., Cortex, 151, ISSN:0010-9452, ISSN:1973-8102

The article at hand aggregates the work of our group in automatic processing of simplified German. We present four parallel (standard/simplified German) corpora compiled and curated by our group. We report on the creation of a gold standard of sentence alignments from the four sources for evaluating automatic alignment methods on this gold standard. We show that one of the alignment methods performs best on the majority of the data sources. We used two of our corpora as a basis for the first sentence-based neural machine translation (NMT) approach toward automatic simplification of German. In follow-up work, we extended our model to render it capable of explicitly operating on multiple levels of simplified German. We show that using source-side language level labels improves performance with regard to two evaluation metrics commonly applied to measuring the quality of automatic text simplification.

The human auditory system is capable of processing human speech even in situations when it has been heavily degraded, such as during noise-vocoding, when frequency domain-based cues to phonetic content are strongly reduced. This has contributed to arguments that speech processing is highly specialized and likely a de novo evolved trait in humans. Previous comparative research has demonstrated that a language competent chimpanzee was also capable of recognizing degraded speech, and therefore that the mechanisms underlying speech processing may not be uniquely human. However, to form a robust reconstruction of the evolutionary origins of speech processing, additional data from other closely related ape species is needed. Specifically, such data can help disentangle whether these capabilities evolved independently in humans and chimpanzees, or if they were inherited from our last common ancestor. Here we provide evidence of processing of highly varied (degraded and computer-generated) speech in a language competent bonobo, Kanzi. We took advantage of Kanzi’s existing proficiency with touchscreens and his ability to report his understanding of human speech through interacting with arbitrary symbols called lexigrams. Specifically, we asked Kanzi to recognise both human (natural) and computer-generated forms of 40 highly familiar words that had been degraded (noise-vocoded and sinusoidal forms) using a match-to-sample paradigm. Results suggest that—apart from noise-vocoded computer-generated speech—Kanzi recognised both natural and computer-generated voices that had been degraded, at rates significantly above chance. Kanzi performed better with all forms of natural voice speech compared to computer-generated speech. This work provides additional support for the hypothesis that the processing apparatus necessary to deal with highly variable speech, including for the first time in nonhuman animals, computer-generated speech, may be at least as old as the last common ancestor we share with bonobos and chimpanzees.

The Zurich Cognitive Language Processing Corpus (ZuCo) provides eye-tracking and EEG signals from two reading paradigms, normal reading and task-specific reading. We analyze whether machine learning methods are able to classify these two tasks using eye-tracking and EEG features. We implement models with aggregated sentence-level features as well as fine-grained word-level features. We test the models in within-subject and cross-subject evaluation scenarios. All models are tested on the ZuCo 1.0 and ZuCo 2.0 data subsets, which are characterized by differing recording procedures and thus allow for different levels of generalizability. Finally, we provide a series of control experiments to analyze the results in more detail.

Functional psychologists are concerned with the performance of cognitive activities in the real world in relation to cognitive changes in older age. Conversational contexts may mitigate the influence of cognitive aging on the cognitive activity of language production. This study examined effects of familiarity with interlocutors, as a context, on language production in the real world.We collected speech samples using iPhones, where an audio recording app (i.e. Electronically Activated Recorder [EAR]) was installed. Over 31,300 brief audio files (30-second long) were randomly collected across four days from 61 young and 48 healthy older adults in Switzerland. We transcribed the audio files that included participants' speech and manually coded for familiar interlocutors (i.e. significant other, friends, family members) and strangers. We computed scores of vocabulary richness and grammatical complexity from the transcripts using computational linguistics techniques.Bayesian multilevel analyses showed that participants used richer vocabulary and more complex grammar when talking with familiar interlocutors than with strangers. Young adults used more diverse vocabulary than older adults and the age effects remained stable across contexts. Furthermore, older adults produced equally complex grammar as young adults did with the significant other, but simpler grammar than young adults with friends and family members.Familiarity with interlocutors is a promising contextual factor for research on aging and language complexity in the real world. Results were discussed in the context of cognitive aging.