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How various types of focus differ with respect to exhaustivity has been a topic of enduring interest in language studies. However, most of the theoretical work explicating such associations has done so cross-linguistically, and little research has been done on how people process and respond to them during language comprehension. This study therefore investigates the associations between the concept of exhaustivity and three focus types in Chinese (wh, cleft, and only foci) using a trichotomous-response design in two experiments: a forced-choice judgment and a self-paced reading experiment, both with adult native speakers. Its results show that, whether engaged in conscious decision-making or an implicit comprehension process, the participants distinguished only-focus and cleft-focus from wh-focus clearly, and also that there are specific differences between only-focus and cleft-focus in conscious decision-making. This implies that, in terms of the relationship between exhaustivity and the focus types under investigation, cleft-focus and only-focus behave very similarly during language comprehension despite the existence of some fine distinctions between them. In other words, the potential linguistic levels that exhaustivity encodes in Chinese cleft-focus render it more similar to only-focus than to wh-focus. These results are broadly in line with the semantic account that distinguishes cleft from only-focus, i.e., that cleft encodes exhaustivity in not-at-issue presupposition and only-focus encodes exhaustivity in at-issue assertion, while both express semantically encoded exhaustivity, triggering robust language-processing patterns that differ from patterns of wh-focus in Chinese. [ABSTRACT FROM AUTHOR]

Objective: Previous research associated the left inferior frontal cortex with implicit structure learning. The present study tested patients with lesions encompassing the left inferior frontal gyrus (LIFG; including Brodmann areas 44 and 45) to further investigate this cognitive function, notably by using non-verbal material, implicit investigation methods, and by enhancing potential remaining function via dynamic attending. Patients and healthy matched controls were exposed to an artificial pitch grammar in an implicit learning paradigm to circumvent the potential influence of impaired language processing. Methods: Patients and healthy controls listened to pitch sequences generated within a finite-state grammar (exposure phase) and then performed a categorization task on new pitch sequences (test phase). Participants were not informed about the underlying grammar in either the exposure phase or the test phase. Furthermore, the pitch structures were presented in a highly regular temporal context as the beneficial impact of temporal regularity (e.g. meter) in learning and perception has been previously reported. Based on the Dynamic Attending Theory (DAT), we hypothesized that a temporally regular context helps developing temporal expectations that, in turn, facilitate event perception, and thus benefit artificial grammar learning. Results: Electroencephalography results suggest preserved artificial grammar learning of pitch structures in patients and healthy controls. For both groups, analyses of event-related potentials revealed a larger early negativity (100–200 msec post-stimulus onset) in response to ungrammatical than grammatical pitch sequence events. Conclusions: These findings suggest that (i) the LIFG does not play an exclusive role in the implicit learning of artificial pitch grammars, and (ii) the use of non-verbal material and an implicit task reveals cognitive capacities that remain intact despite lesions to the LIFG. These results provide grounds for training and rehabilitation, that is, learning of non-verbal grammars that may impact the relearning of verbal grammars. [ABSTRACT FROM AUTHOR]

This paper describes the process of adapting the Stanford Coreference resolution module to the Basque language, taking into account the characteristics of the language. The module has been integrated in a linguistic analysis pipeline obtaining an end-to-end coreference resolution system for the Basque language. The adaptation process explained can benefit and facilitate other languages with similar characteristics in the implementation of their coreference resolution systems. During the experimentation phase, we have demonstrated that language-specific features have a noteworthy effect on coreference resolution, obtaining a gain in CoNLL score of 7.07 with respect to the baseline system. We have also analysed the effect that preprocessing has in coreference resolution, comparing the results obtained with automatic mentions versus gold mentions. When gold mentions are provided, the results increase 11.5 points in CoNLL score in comparison with results obtained when automatic mentions are used. The contribution of each sieve is analysed concluding that morphology is essential for agglutinative languages to obtain good performance in coreference resolution. Finally, an error analysis of the coreference resolution system is presented which have revealed our system’s weak points and help to determine the improvements of the system. As a result of the error analysis, we have enriched the Basque coreference resolution adding new two sieves, obtaining an improvement of 0.24 points in CoNLL F1 when automatic mentions are used and of 0.39 points when the gold mentions are provided. [ABSTRACT FROM AUTHOR]

Lately, discourse structure has received considerable attention due to the benefits its application offers in several NLP tasks such as opinion mining, summarization, question answering, text simplification, among others. When automatically analyzing texts, discourse parsers typically perform two different tasks: i) identification of basic discourse units (text segmentation) ii) linking discourse units by means of discourse relations, building structures such as trees or graphs. The resulting discourse structures are, in general terms, accurate at intra-sentence discourse-level relations, however they fail to capture the correct inter-sentence relations. Detecting the main discourse unit (the Central Unit) is helpful for discourse analyzers (and also for manual annotation) in improving their results in rhetorical labeling. Bearing this in mind, we set out to build the first two steps of a discourse parser following a top-down strategy: i) to find discourse units, ii) to detect the Central Unit. The final step, i.e. assigning rhetorical relations, remains to be worked on in the immediate future. In accordance with this strategy, our paper presents a tool consisting of a discourse segmenter and an automatic Central Unit detector. [ABSTRACT FROM AUTHOR]

Big web data from sources including online news and Twitter are good resources for investigating deep learning. However, collected news articles and tweets almost certainly contain data unnecessary for learning, and this disturbs accurate learning. This paper explores the performance of word2vec Convolutional Neural Networks (CNNs) to classify news articles and tweets into related and unrelated ones. Using two word embedding algorithms of word2vec, Continuous Bag-of-Word (CBOW) and Skip-gram, we constructed CNN with the CBOW model and CNN with the Skip-gram model. We measured the classification accuracy of CNN with CBOW, CNN with Skip-gram, and CNN without word2vec models for real news articles and tweets. The experimental results indicated that word2vec significantly improved the accuracy of the classification model. The accuracy of the CBOW model was higher and more stable when compared to that of the Skip-gram model. The CBOW model exhibited better performance on news articles, and the Skip-gram model exhibited better performance on tweets. Specifically, CNN with word2vec models was more effective on news articles when compared to that on tweets because news articles are typically more uniform when compared to tweets. [ABSTRACT FROM AUTHOR]

The linguistic environment of the classroom is influential to young children’s language development. To date, however, literature on the linguistic environment of child-care centers has largely examined teacher practices or children’s aggregate environment, overlooking the child’s first-person experiences and differentiated experiences within the classroom. In this study we used a new method in the educational setting that captures the learner’s perspective: head-mounted cameras. Thirteen children in one preschool classroom wore a head-mounted camera to capture their first-person experiences in one morning session, including interactions with others and the features of the child-directed speech (CDS) addressed to them. Results revealed that, from children’s personal view, the linguistic environment of the classroom is more dynamic from what previous studies have reported. Children interacted for longer with their teachers than their peers and heard more CDS from them, but for some children peers served as an additional source of language. Further, our analysis highlighted within-classroom variability in language experiences in terms of the properties of the CDS addressed to target children and how they were exposed to this input over time. Results are discussed with respect to peer influence on children’s learning, heterogeneity in learning opportunities in classrooms, and the variability of the linguistic environment over time. [ABSTRACT FROM AUTHOR]

Objective: This study aimed to compare the levels of plasma neutrophil gelatinase-associated lipocalin (NGAL), matrix metalloproteinase (MMP)-9, high-sensitivity C-reactive protein (hs-CRP), and interleukin (IL)-1β across different clinical presentations of coronary artery disease and to evaluate the relationship between those biomarkers and the severity of coronary artery lesions in patients without kidney disease. Methods: We examined 365 eligible patients who underwent coronary angiography. A total of 124 ST-segment elevation myocardial infarction (STEMI) patients, 117 stable angina pectoris (SAP) patients and 124 patients without atherosclerotic plaques were enrolled in the study. Plasma NGAL, MMP-9, hs-CRP, and IL-1β were measured in all patients using the enzyme-linked immunosorbent assay (ELISA) method. According to the SYNTAX score, the STEMI patients and SAP patients were divided into another set of 2 groups: a high score group (≥ 33, n = 29) and a low score group (<33, n = 212). The relationship between those biomarkers and the severity of coronary stenosis was examined by Spearman correlation analysis; the ability for NGAL to discriminate severe coronary stenosis was examined by receiver operating characteristic (ROC) curve; the influencing factors for the SYNTAX score were determined by logistic regression analysis. Results: Plasma NGAL, MMP-9, and hs-CRP levels in STEMI patients were higher than in the SAP patients and control subjects (P<0.05, respectively), and plasma NGAL and hs-CRP levels were significantly higher in the SAP patients than in control subjects (P<0.05, respectively), while plasma IL-1β was similar among the 3 groups (P>0.05, respectively). The SYNTAX score was positively related to NGAL (r = 0.363, P<0.001), MMP-9 (r = 0.377, P<0.001), and hs-CRP (r = 0.163, P<0.011); the SYNTAX score was not related to IL-1β (r = -0.043, P = 0.510). Plasma NGAL was positively related to MMP-9 (r = 0.601, P<0.001) and IL-1β (r = 0.159, P = 0.014). The area under the ROC curve for NGAL discriminating severe coronary stenosis was 0.838 (95% CI: 0.752–0.923, P<0.001), which was greater than that for MMP-9 [0.818, (95% CI: 0.724–0.912, P<0.001)], IL-1β [0.485, (95% CI: 0.369–0.601, P = 0.791)], and hs-CRP [0.607, (95% CI: 0.492–0.722, P = 0.061)]. Multivariate regression analysis showed that plasma NGAL levels were independently related to high SYNTAX scores [OR = 1.109, (95% CI: 1.104–1.114), P<0.001]. Conclusion: Plasma NGAL, MMP-9, and hs-CRP levels in STEMI patients were higher than those in the SAP patients and control subjects. NGAL had a better ability to discriminate severe coronary stenosis than MMP-9, IL-1β, and hs-CRP. NGAL may be a novel biomarker to aid in risk stratification in coronary heart disease patients. [ABSTRACT FROM AUTHOR]

Statistical learning (SL) difficulties have been suggested to contribute to the linguistic and non-linguistic problems observed in children with dyslexia. Indeed, studies have demonstrated that children with dyslexia experience problems with SL, but the extent of the problems is unclear. We aimed to examine the performance of children with and without dyslexia across three distinct paradigms using both on- and offline measures, thereby tapping into different aspects of SL. 100 children with and without dyslexia (aged 8–11, 50 per group) completed three SL tasks: serial reaction time (SRT), visual statistical learning (VSL), and auditory nonadjacent dependency learning (A-NADL). Learning was measured through online reaction times during exposure in all tasks, and through offline questions in the VSL and A-NADL tasks. We find significant learning effects in all three tasks, from which we conclude that, collapsing over groups, children are sensitive to the statistical structures presented in the SRT, VSL and A-NADL tasks. No significant interactions of learning effect with group were found in any of the tasks, so we cannot conclude whether or not children with dyslexia perform differently on the SL tasks than their TD peers. These results are discussed in light of the proposed SL deficit in dyslexia. [ABSTRACT FROM AUTHOR]

Where readers move their eyes, while proceeding forward along lines of text, has long been assumed to be determined in a top-down word-based manner. According to this classical view, readers of alphabetic languages would invariably program their saccades towards the center of peripheral target words, as selected based on the (expected) needs of ongoing (word-identification) processing, and the variability in within-word landing positions would exclusively result from systematic and random errors. Here we put this predominant hypothesis to a strong test by estimating the respective influences of language-related variables (word frequency and word predictability) and lower-level visuo-motor factors (word length and saccadic launch-site distance to the beginning of words) on both word-skipping likelihood and within-word landing positions. Our eye-movement data were collected while forty participants read 316 pairs of sentences, that differed only by one word, the prime; this was either semantically related or unrelated to a following test word of variable frequency and length. We found that low-level visuo-motor variables largely predominated in determining which word would be fixated next, and where in a word the eye would land. In comparison, language-related variables only had tiny influences. Yet, linguistic variables affected both the likelihood of word skipping and within-word initial landing positions, all depending on the words’ length and how far on average the eye landed from the word boundaries, but pending the word could benefit from peripheral preview. These findings provide a strong case against the predominant word-based account of eye-movement guidance during reading, by showing that saccades are primarily driven by low-level visuo-motor processes, regardless of word boundaries, while being overall subject to subtle, one-off, language-based modulations. Our results also suggest that overall distributions of saccades’ landing positions, instead of truncated within-word landing-site distributions, should be used for a better understanding of eye-movement guidance during reading. [ABSTRACT FROM AUTHOR]

This paper investigates a particular type of non-canonical construction in Mandarin Chinese displaying an apparent semantics-syntax mismatch. We conducted an acceptability judgment experiment on native Mandarin speakers to evaluate whether such sequences could stand out of context as acceptable fragments. Analyses on experimental results revealed that: both semantic and syntactic acceptability of these sequences were significantly lower than those of canonical nominal classifier phrases; whereas if contextualized, the syntactic acceptability of those sequences became similar to that of canonical nominal phrases. This suggests that the non-canonical sequences are grammatically not on the same footing as canonical expressions; and it is the sentential context that makes these sequences appear structurally well-formed. These findings contribute to general discussions on relationship between constituency and grammaticality by demonstrating the gradient nature of grammaticality, and advocate a dynamic perspective in linguistic analysis that looks at a sequence of words in interaction with other elements in a sentence. [ABSTRACT FROM AUTHOR]

The mature lexicon encodes semantic relations between words, and these connections can alternately facilitate and interfere with language processing. We explore the emergence of these processing dynamics in 18-month-olds (N = 79) using a novel approach that calculates individualized semantic structure at multiple granularities in participants’ productive vocabularies. Participants completed two interleaved eye-tracked word recognition tasks involving semantically unrelated and related picture contexts, which sought to measure the impact of lexical facilitation and interference on processing, respectively. Semantic structure and vocabulary size differentially impacted processing in each task. Category level structure facilitated word recognition in 18-month-olds with smaller productive vocabularies, while overall lexical connectivity interfered with word recognition for toddlers with relatively larger vocabularies. The results suggest that, while semantic structure at multiple granularities is measurable even in small lexicons, mechanisms of semantic interference and facilitation are driven by the development of structure at different granularities. We consider these findings in light of accounts of adult word recognition that posits that different levels of structure index strong and weak activation from nearby and distant semantic neighbors. We also consider further directions for developmental change in these patterns. [ABSTRACT FROM AUTHOR]

Tonal harmony is one of the central organization systems of Western music. This article characterizes the statistical foundations of tonal harmony based on the computational analysis of expert annotations in a large corpus. Using resampling methods, this study shows that 1) the rank-frequency distribution of chords resembles a power law, i.e. few chords govern a large proportion of the data; 2) chord transitions are referential and chord predictability is significantly affected by distinguished chord features; 3) tonal harmony conveys directedness in time; and 4) tonal harmony operates differently at the hierarchical levels of chords and keys. These results serve to characterize tonal harmony on empirical grounds and advance the methodological state-of-the-art in digital musicology. [ABSTRACT FROM AUTHOR]

Everyday speech is produced with an intricate timing pattern and rhythm. Speech units follow each other with short interleaving pauses, which can be either bridged by fillers (erm, ah) or empty. Through their syntactic positions, pauses connect to the thoughts expressed. We investigated whether disturbances of thought in schizophrenia are manifest in patterns at this level of linguistic organization, whether these are seen in first degree relatives (FDR) and how specific they are to formal thought disorder (FTD). Spontaneous speech from 15 participants without FTD (SZ-FTD), 15 with FTD (SZ+FTD), 15 FDRs and 15 neurotypical controls (NC) was obtained from a comic strip retelling task and rated for pauses subclassified by syntactic position and duration. SZ-FTD produced significantly more unfilled pauses than NC in utterance-initial positions and before embedded clauses. Unfilled pauses occurring within clausal units did not distinguish any groups. SZ-FTD also differed from SZ+FTD in producing significantly more pauses before embedded clauses. SZ+FTD differed from NC and FDR only in producing longer utterance-initial pauses. FDRs produced significantly fewer fillers than NC. Results reveal that the temporal organization of speech is an important window on disturbances of the thought process and how these relate to language. [ABSTRACT FROM AUTHOR]

There is extensive evidence showing that bilinguals activate the lexical and the syntactic representations of both languages in a nonselective way. However, the extent to which the lexical and the syntactic levels of representations interact during second language (L2) sentence processing and how those interactions are modulated by L2 proficiency remain unclear. This paper aimed to directly address these issues by using an online technique (eye-tracking) that is highly sensitive to the lexical and syntactic processes involved in sentence reading. To that purpose, native-speakers of European Portuguese (EP) learning English as L2 at intermediate and advanced levels of proficiency were asked to silently read temporally ambiguous L2 relative clause (RC) sentences disambiguated with a High-Attachment (HA) or Low-Attachment (LA) strategy while their eye-movements were monitored. Since EP and English native speakers differ in the way they process and comprehend this syntactic structure (EP: HA, English: LA), HA preferences were used as a marker of L1 RC syntax interference. Additionally, the cognate status of the complex NP that preceded the RC was manipulated to further analyze how the lexical co-activation of both languages would also affect the syntactic representations of the non-target (L1) language. Results showed cognate facilitation in early and late reading time measures regardless of L2 proficiency, and also that the cognate status of the complex NP impacted L2 reading performance, particularly at lower levels of L2 proficiency. These findings provide compelling evidence for a bilingual reading system that seems to be highly dynamic and interactive not only within each level of processing, but, importantly, across levels of representation. They also suggested that, as the level of L2 proficiency increases, L1 RC syntax interference becomes stronger, in a syntactic parser that seems to operate in a more integrated and nonselective way, with both strategies being equally available to guide L2 reading comprehension. Results are discussed attending to the current models of bilingual syntactic processing. [ABSTRACT FROM AUTHOR]

We study the relative importance of the three dimensions of need-supportive teaching (NST) and students’ self-efficacy to gain new knowledge about students’ achievement in higher education. NST assumes that teachers are key to the motivation of students, providing autonomy support, structure (support of competence), and involvement (support of relatedness). In turn, self-efficacy raises students’ confidence in their ability to succeed in academic tasks. Drawing on 86,000 records of teaching evaluations by students at the University of Girona (Spain), we present evidence that teachers’ involvement and students’ self-efficacy are the two elements most strongly and positively related to achievement. Students obtain higher marks when they believe that their teachers are dependable and available to offer resources, and when they feel capable of organizing and implementing the courses of action necessary to acquire knowledge. We also find that students’ experience of autonomy support and structure are negatively (or not) correlated with achievement. Subgroup analyses also indicate that students have different needs in different knowledge areas. [ABSTRACT FROM AUTHOR]

In this paper, we propose an Emotional Trigger System to impart an automatic emotion expression ability within the humanoid robot REN-XIN, in which the Emotional Trigger is an emotion classification model trained from our proposed Word Mover’s Distance(WMD) based algorithm. Due to the long time delay of the WMD-based Emotional Trigger System, we propose an enhanced Emotional Trigger System to enable a smooth interaction with the robot in which the Emotional Trigger is replaced by a conventional convolution neural network and a long short term memory network (CNN_LSTM)-based deep neural network. In our experiments, the CNN_LSTM based model only need 10 milliseconds or less to finish the classification without a decrease in accuracy, while the WMD-based model needed approximately 6-8 seconds to give a result. In this paper, the experiments are conducted based on the same sub-data sets of the Chinese emotional corpus(Ren_CECps) used in former WMD experiments: one comprises 50% data for training and 50% for testing(1v1 experiment), and the other comprises 80% data for training and 20% for testing(4v1 experiment). The experiments are conducted using WMD, CNN_LSTM, CNN and LSTM. The results show that CNN_LSTM obtains the best F1 score (0.35) in the 1v1 experiment and almost the same accuracy of F1 scores (0.366 vs 0.367) achieved by WMD in the 4v1 experiment. Finally, we present demonstration videos with the same scenario to show the performance of robot control driven by CNN_LSTM-based Emotional Trigger System and WMD-based Emotional Trigger System. To improve the comparison, total manual-control performance is also recorded. [ABSTRACT FROM AUTHOR]

Language is one the earliest capacities affected by cognitive change. To monitor that change longitudinally, we have developed a web portal for remote linguistic data acquisition, called Talk2Me, consisting of a variety of tasks. In order to facilitate research in different aspects of language, we provide baselines including the relations between different scoring functions within and across tasks. These data can be used to augment studies that require a normative model; for example, we provide baseline classification results in identifying dementia. These data are released publicly along with a comprehensive open-source package for extracting approximately two thousand lexico-syntactic, acoustic, and semantic features. This package can be applied arbitrarily to studies that include linguistic data. To our knowledge, this is the most comprehensive publicly available software for extracting linguistic features. The software includes scoring functions for different tasks. [ABSTRACT FROM AUTHOR]

A recent semantic theory of nominal concepts by Löbner [] posits that–due to their inherent uniqueness and relationality properties–noun concepts can be classified into four concept types (CTs): sortal, individual, relational, functional. For sortal nouns the default determination is indefinite (a stone), for individual nouns it is definite (the sun), for relational and functional nouns it is possessive (his ear, his father). Incongruent determination leads to a concept type shift: his father (functional concept: unique, relational)–a father (sortal concept: non-unique, non-relational). Behavioral studies on CT shifts have demonstrated a CT congruence effect, with congruent determiners triggering faster lexical decision times on the subsequent noun than incongruent ones [, ]. The present ERP study investigated electrophysiological correlates of congruent and incongruent determination in German noun phrases, and specifically, whether the CT congruence effect could be indexed by such classic ERP components as N400, LAN or P600. If incongruent determination affects the lexical retrieval or semantic integration of the noun, it should be reflected in the amplitude of the N400 component. If, however, CT congruence is processed by the same neuronal mechanisms that underlie morphosyntactic processing, incongruent determination should trigger LAN or/and P600. These predictions were tested in two ERP studies. In Experiment 1, participants just listened to noun phrases. In Experiment 2, they performed a wellformedness judgment task. The processing of (in)congruent CTs (his sun vs. the sun) was compared to the processing of morphosyntactic and semantic violations in control conditions. Whereas the control conditions elicited classic electrophysiological violation responses (N400, LAN, & P600), CT-incongruences did not. Instead they showed novel concept-type specific response patterns. The absence of the classic ERP components suggests that CT-incongruent determination is not perceived as a violation of the semantic or morphosyntactic structure of the noun phrase. [ABSTRACT FROM AUTHOR]

Human listeners can focus on one speech stream out of several concurrent ones. The present study aimed to assess the whole-brain functional networks underlying a) the process of focusing attention on a single speech stream vs. dividing attention between two streams and 2) speech processing on different time-scales and depth. Two spoken narratives were presented simultaneously while listeners were instructed to a) track and memorize the contents of a speech stream and b) detect the presence of numerals or syntactic violations in the same (“focused attended condition”) or in the parallel stream (“divided attended condition”). Speech content tracking was found to be associated with stronger connectivity in lower frequency bands (delta band- 0,5–4 Hz), whereas the detection tasks were linked with networks operating in the faster alpha (8–10 Hz) and beta (13–30 Hz) bands. These results suggest that the oscillation frequencies of the dominant brain networks during speech processing may be related to the duration of the time window within which information is integrated. We also found that focusing attention on a single speaker compared to dividing attention between two concurrent speakers was predominantly associated with connections involving the frontal cortices in the delta (0.5–4 Hz), alpha (8–10 Hz), and beta bands (13–30 Hz), whereas dividing attention between two parallel speech streams was linked with stronger connectivity involving the parietal cortices in the delta and beta frequency bands. Overall, connections strengthened by focused attention may reflect control over information selection, whereas connections strengthened by divided attention may reflect the need for maintaining two streams in parallel and the related control processes necessary for performing the tasks. [ABSTRACT FROM AUTHOR]

Background: In this paper we present a model of parameters to aesthetically characterize films using a multi-disciplinary approach: by combining film theory, visual low-level video descriptors (modeled in order to supply aesthetic information) and classification techniques using machine and deep learning. Methods: Four different tests have been developed, each for a different application, proving the model's usefulness. These applications are: aesthetic style clustering, prediction of production year, genre detection and influence on film popularity. Results: The results are compared against high-level information to determine the accuracy of the model to classify films without knowing such information previously. The main difference with other film characterization approaches is that we are able to isolate the influence of high-level descriptors to really understand the relevance of low-level features and, accordingly propose a useful set of low-level visual descriptors for that purpose. This model has been tested with a representative number of films to prove that it can be used for different applications. [ABSTRACT FROM AUTHOR]

Urban public spaces facilitate social interactions between people, reflecting the shifting functionality of spaces. There is no commonly-held consensus on the quantification methods for the dynamic interplay between spatial geometry, urban movement, and face-to-face encounters. Using anonymized social media check-in records from Shanghai, China, this study proposes pipelines for quantifying physical face-to-face encounter potential patterns through public space networks between local and non-local residents sensed by social media over time from space to space, in which social difference, cognitive cost, and time remoteness are integrated as the physical co-presence intensity index. This illustrates the spatiotemporally different ways in which the built environment binds various groups of space users configurationally via urban streets. The variation in face-to-face interaction patterns captures the fine-resolution patterns of urban flows and a new definition of street hierarchy, illustrating how urban public space systems deliver physical meeting opportunities and shape the spatial rhythms of human behavior from the public to the private. The shifting encounter potentials through streets are recognized as reflections of urban centrality structures with social interactions that are spatiotemporally varying, projected in the configurations of urban forms and functions. The results indicate that the occurrence probability of face-to-face encounters is more geometrically scaled than predicted based on the co-location probability of two people using metric distance alone. By adding temporal and social dimensions to urban morphology studies, and the field of space syntax research in particular, we suggest a new approach of analyzing the temporal urban centrality structures of the physical interaction potentials based on trajectory data, which is sensitive to the transformation of the spatial grid. It sheds light on how to adopt urban design as a social instrument to facilitate the dynamically changing social interaction potential in the new data environment, thereby enhancing spatial functionality and the social well-being. [ABSTRACT FROM AUTHOR]

Despite the extensive literature investigating stylometry analysis in authorship attribution research, translator stylometry is an understudied research area. The identification of translator stylometry contributes to many fields including education, intellectual property rights and forensic linguistics. In a two stage process, this paper first evaluates the use of existing lexical measures for the translator stylometry problem. Similar to previous research we found that using vocabulary richness in its traditional form as it has been used in the literature could not identify translator stylometry. This encouraged us to design an approach with the aim of identifying the distinctive patterns of a translator by employing network-motifs. Networks motifs are small sub-graphs which aim at capturing the local structure of a complex network. The proposed approach achieved an average accuracy of 83% in three-way classification. These results demonstrate that classic tools based on lexical features can be used for identifying translator stylometry if they get augmented with appropriate non-parametric scaling. Moreover, the use of complex network analysis and network motifs mining provided made it possible to design features that can solve translator stylometry analysis problems. [ABSTRACT FROM AUTHOR]

Reading research uses different tasks to investigate different levels of the reading process, such as word recognition, syntactic parsing, or semantic integration. It seems to be tacitly assumed that the underlying cognitive process that constitute reading are stable across those tasks. However, nothing is known about what happens when readers switch from one reading task to another. The stability assumptions of the reading process suggest that the cognitive system resolves this switching between two tasks quickly. Here, we present an alternative language-game hypothesis (LGH) of reading that begins by treating reading as a softly-assembled process and that assumes, instead of stability, context-sensitive flexibility of the reading process. LGH predicts that switching between two reading tasks leads to longer lasting phase-transition like patterns in the reading process. Using the nonlinear-dynamical tool of recurrence quantification analysis, we test these predictions by examining series of individual word reading times in self-paced reading tasks where native (L1) and second language readers (L2) transition between random word and ordered text reading tasks. We find consistent evidence for phase-transitions in the reading times when readers switch from ordered text to random-word reading, but we find mixed evidence when readers transition from random-word to ordered-text reading. In the latter case, L2 readers show moderately stronger signs for phase-transitions compared to L1 readers, suggesting that familiarity with a language influences whether and how such transitions occur. The results provide evidence for LGH and suggest that the cognitive processes underlying reading are not fully stable across tasks but exhibit soft-assembly in the interaction between task and reader characteristics. [ABSTRACT FROM AUTHOR]

The purpose of this study was to investigate the effects of playing position, pitch location, team ability and opposition ability on technical performance variables (pass, cross, corner, free kick accuracy) of English Premier League Soccer players in difference score line states. A validated automatic tracking system (Venatrack) was used to code player actions in real time for passing accuracy, cross accuracy, corner accuracy and free kick accuracy. In total 376 of the 380 games played during the 2011–12 English premier League season were recorded, resulting in activity profiles of 570 players and over 35’000 rows of data. These data were analysed using multi-level modelling. Multi-level regression revealed a “u” shaped association between passing accuracy and goal difference (GD) with greater accuracy occurring at extremes of GD e.g., when the score was either positive or negative. The same pattern was seen for corner accuracy away from home e.g., corner accuracy was lowest when the score was close with the lowest accuracy at extremes of GD. Although free kicks were not associated with GD, team ability, playing position and pitch location were found to predict accuracy. No temporal variables were found to predict cross accuracy. A number of score line effects were present across the temporal factors which should be considered by coaches and managers when preparing and selecting teams in order to maximise performance. The current study highlighted the need for more sensitive score line definitions in which to consider score line effects. [ABSTRACT FROM AUTHOR]

Sea noise collected over 2003 to 2017 from the Perth Canyon, Western Australia was analysed for variation in the South Eastern Indian Ocean pygmy blue whale song structure. The primary song-types were: P3, a three unit phrase (I, II and III) repeated with an inter-song interval (ISI) of 170–194 s; P2, a phrase consisting of only units II & III repeated every 84–96 s; and P1 with a phrase consisting of only unit II repeated every 45–49 s. The different ISI values were approximate multiples of each other within a season. When comparing data from each season, across seasons, the ISI value for each song increased significantly through time (all fits had p << 0.001), at 0.30 s/Year (95%CI 0.217–0.383), 0.8 s/Year (95%CI 0.655–1.025) and 1.73 s/Year (95%CI 1.264–2.196) for the P1, P2 and P3 songs respectively. The proportions of each song-type averaged at 21.5, 24.2 and 56% for P1, P2 and P3 occurrence respectively and these ratios could vary by up to ± 8% (95% CI) amongst years. On some occasions animals changed the P3 ISI to be significantly shorter (120–160 s) or longer (220–280 s). Hybrid song patterns occurred where animals combined multiple phrase types into a repeated song. In recent years whales introduced further complexity by splitting song units. This variability of song-type and proportions implies abundance measure for this whale sub population based on song detection needs to factor in trends in song variability to make data comparable between seasons. Further, such variability in song production by a sub population of pygmy blue whales raises questions as to the stability of the song types that are used to delineate populations. The high level of song variability may be driven by an increasing number of background whale callers creating ‘noise’ and so forcing animals to alter song in order to ‘stand out’ amongst the crowd. [ABSTRACT FROM AUTHOR]

In many offline studies, children show selectively better comprehension of sentences with the focus particle only when it modifies the object argument (Jane only ate ) than they do when it modifies the subject argument (Only ate an apple). Here we explore the nature of this asymmetry by examining performance in a different kind of task: the moment-to-moment comprehension of unambiguous sentences. If past errors reflect a fundamental difference in representation or complexity of computation, we would expect the same asymmetry in this task. We observed that adults were able to successfully predict the target referent for both types of only-sentences, as indicated by anticipatory looks, while 6- to 8-year-old children could do so only for subject-modifying only-sentences. These findings suggest that much of the asymmetry in past work may be due to task demands. We discuss the implications of these results for children’s syntactic and pragmatic development. [ABSTRACT FROM AUTHOR]

The grammar, or syntax, of human language is typically understood in terms of abstract hierarchical structures. However, theories of language processing that emphasize sequential information, not hierarchy, successfully model diverse phenomena. Recent work probing brain signals has shown mixed evidence for hierarchical information in some tasks. We ask whether sequential or hierarchical information guides the expectations that a human listener forms about a word’s part-of-speech when simply listening to every-day language. We compare the predictions of three computational models against electroencephalography signals recorded from human participants who listen passively to an audiobook story. We find that predictions based on hierarchical structure correlate with the human brain response above-and-beyond predictions based only on sequential information. This establishes a link between hierarchical linguistic structure and neural signals that generalizes across the range of syntactic structures found in every-day language. [ABSTRACT FROM AUTHOR]

Introduction: Surveys indicate that patients, particularly those suffering from chronic conditions, strongly benefit from the information found in social networks and online forums. One challenge in accessing online health information is to differentiate between factual and more subjective information. In this work, we evaluate the feasibility of exploiting lexical, syntactic, semantic, network-based and emotional properties of texts to automatically classify patient-generated contents into three types: “experiences”, “facts” and “opinions”, using machine learning algorithms. In this context, our goal is to develop automatic methods that will make online health information more easily accessible and useful for patients, professionals and researchers. Material and methods: We work with a set of 3000 posts to online health forums in breast cancer, morbus crohn and different allergies. Each sentence in a post is manually labeled as “experience”, “fact” or “opinion”. Using this data, we train a support vector machine algorithm to perform classification. The results are evaluated in a 10-fold cross validation procedure. Results: Overall, we find that it is possible to predict the type of information contained in a forum post with a very high accuracy (over 80 percent) using simple text representations such as word embeddings and bags of words. We also analyze more complex features such as those based on the network properties, the polarity of words and the verbal tense of the sentences and show that, when combined with the previous ones, they can boost the results. [ABSTRACT FROM AUTHOR]

Demonstrative reference is central to human communication. But what influences our choice of demonstrative forms such as “this” and “that” in discourse? Previous literature has mapped the use of such “proximal” and “distal” demonstratives onto spatial properties of referents, such as their distance from the speaker. We investigated whether object semantics, and specifically functional properties of referents, also influence speakers’ choices of either demonstrative form. Over two experiments, we presented English, Danish and Italian speakers with words denoting animate and inanimate objects, differing in size and harmfulness, and asked them to match them with a proximal or a distal demonstrative. Objects that offer more affordances for manipulation (smaller and harmless) elicited significantly more proximal demonstratives. These effects were stronger for inanimate referents, in line with the predictions of sensory-functional views on object semantics. These results suggest that demonstrative use may be partly grounded on manual affordances, and hints at the possibility of using demonstratives as a proxy to investigate the organization of semantic knowledge. [ABSTRACT FROM AUTHOR]

This article explores how probabilistic programming can be used to simulate quantum correlations in an EPR experimental setting. Probabilistic programs are based on standard probability which cannot produce quantum correlations. In order to address this limitation, a hypergraph formalism was programmed which both expresses the measurement contexts of the EPR experimental design as well as associated constraints. Four contemporary open source probabilistic programming frameworks were used to simulate an EPR experiment in order to shed light on their relative effectiveness from both qualitative and quantitative dimensions. We found that all four probabilistic languages successfully simulated quantum correlations. Detailed analysis revealed that no language was clearly superior across all dimensions, however, the comparison does highlight aspects that can be considered when using probabilistic programs to simulate experiments in quantum physics. [ABSTRACT FROM AUTHOR]

Brain-Computer Interfaces (BCIs) have become more and more popular these last years. Researchers use this technology for several types of applications, including attention and workload measures but also for the direct control of objects by the means of BCIs. In this work we present a first, multidimensional feature space for EEG-based BCI applications to help practitioners to characterize, compare and design systems, which use EEG-based BCIs. Our feature space contains 4 axes and 9 sub-axes and consists of 41 options in total as well as their different combinations. We presented the axes of our feature space and we positioned our feature space regarding the existing BCI and HCI taxonomies and we showed how our work integrates the past works, and/or complements them. [ABSTRACT FROM AUTHOR]

Word sense disambiguation (WSD) is the process of identifying an appropriate sense for an ambiguous word. With the complexity of human languages in which a single word could yield different meanings, WSD has been utilized by several domains of interests such as search engines and machine translations. The literature shows a vast number of techniques used for the process of WSD. Recently, researchers have focused on the use of meta-heuristic approaches to identify the best solutions that reflect the best sense. However, the application of meta-heuristic approaches remains limited and thus requires the efficient exploration and exploitation of the problem space. Hence, the current study aims to propose a hybrid meta-heuristic method that consists of particle swarm optimization (PSO) and simulated annealing to find the global best meaning of a given text. Different semantic measures have been utilized in this model as objective functions for the proposed hybrid PSO. These measures consist of JCN and extended Lesk methods, which are combined effectively in this work. The proposed method is tested using a three-benchmark dataset (SemCor 3.0, SensEval-2, and SensEval-3). Results show that the proposed method has superior performance in comparison with state-of-the-art approaches. [ABSTRACT FROM AUTHOR]

Language processing requires us to integrate incoming linguistic representations with representations of past input, often across intervening words and phrases. This computational situation has been argued to require retrieval of the appropriate representations from memory via a set of features or representations serving as retrieval cues. However, even within in a cue-based retrieval account of language comprehension, both the structure of retrieval cues and the particular computation that underlies direct-access retrieval are still underspecified. Evidence from two event-related brain potential (ERP) experiments that show cue-based interference from different types of linguistic representations during ellipsis comprehension are consistent with an architecture wherein different cue types are integrated, and where the interaction of cue with the recent contents of memory determines processing outcome, including expression of the interference effect in ERP componentry. I conclude that retrieval likely includes a computation where cues are integrated with the contents of memory via a linear weighting scheme, and I propose vector addition as a candidate formalization of this computation. I attempt to account for these effects and other related phenomena within a broader cue-based framework of language processing. [ABSTRACT FROM AUTHOR]

Emotions have crucial influence on vocabulary learning and text comprehension. However, whether morphosyntactic learning is influenced by emotional conditions has remained largely unclear. In this study, we investigated how induced positive and negative emotions affect the learning of morphosyntactic rules in a foreign language. It was found that negative emotion increased the accuracy and efficiency of syntactic learning, but had no significant effect on the learning of morphological marking rules. Positive emotion was not found to be significantly associated with learning outcomes. The findings shed light on the effects of affective states on the structural aspects of foreign language learning. [ABSTRACT FROM AUTHOR]

A numeral classifier is required between a numeral and a noun in Chinese, which comes in two varieties, sortal classifier (C) and mensural classifier (M). A recent linguistic theory suggests that C/Ms carry quantity information, where C and M converge as the multiplicand, with numeral as the multiplier, but C and M diverge in the mathematical values they denote. However, previous empirical studies were sparse and presented inconsistent results. This study aimed to investigate the mathematical function of C/Ms using the number-size task in which participants had to choose from two C/M phrases the one that represents a larger quantity or in a larger font size. If C/M phrases engage quantity processing like numbers, distance and congruity effects should emerge. As expected, participants performed more accurately and faster at comparing two distant stimuli than two proximate ones, indicating that the mathematical values of C/M were represented like a mental number line. Moreover, participants' performance was partially influenced by the irrelevant information from the other dimension, suggesting that the mathematical values of C/Ms and the physical font size interfere with each other. These results corroborated that C/Ms play a role in magnitude cognition. [ABSTRACT FROM AUTHOR]

Two studies are presented that investigate the effect of linguistic cues on Mandarin speakers’ comprehension of transitive constructions. Study 1 investigated Mandarin-speaking 2- to 4-year-olds’ and adults’ comprehension of the SVO (Subject-verb-object) construction, ba-construction (SbaOV), and subjectless ba-construction ((S)baOV) with novel verbs using the forced choice pointing paradigm (FCPP). Study 2 investigated another group of participants with similar ages’ comprehension of the SVO construction, the ba-construction, the long and short passive constructions with novel verbs and FCPP. Although these constructions have differing cue strengths, participants in the same age groups comprehended these construction types equally well. The results suggest that children as young as two attended to the case markers of ba and bei, allowing them to employ abstract syntactic representations in comprehending Mandarin transitive constructions. The findings demonstrate that children are sensitive early on to the structural information encoded in the constructions. [ABSTRACT FROM AUTHOR]

Research on the music-language interface has extensively investigated similarities and differences of poetic and musical meter, but largely disregarded melody. Using a measure of melodic structure in music––autocorrelations of sound sequences consisting of discrete pitch and duration values––, we show that individual poems feature distinct and text-driven pitch and duration contours, just like songs and other pieces of music. We conceptualize these recurrent melodic contours as an additional, hitherto unnoticed dimension of parallelistic patterning. Poetic speech melodies are higher order units beyond the level of individual syntactic phrases, and also beyond the levels of individual sentences and verse lines. Importantly, auto-correlation scores for pitch and duration recurrences across stanzas are predictive of how melodious naive listeners perceive the respective poems to be, and how likely these poems were to be set to music by professional composers. Experimentally removing classical parallelistic features characteristic of prototypical poems (rhyme, meter, and others) led to decreased autocorrelation scores of pitches, independent of spoken renditions, along with reduced ratings for perceived melodiousness. This suggests that the higher order parallelistic feature of poetic melody strongly interacts with the other parallelistic patterns of poems. Our discovery of a genuine poetic speech melody has great potential for deepening the understanding of the music-language interface. [ABSTRACT FROM AUTHOR]

Understanding the sense of discourse relations between segments of text is essential to truly comprehend any natural language text. Several automated approaches have been suggested, but all rely on external resources, linguistic feature engineering, and their processing pipelines are built from substantially different models. In this paper, we introduce a novel system for sense classification of shallow discourse relations (FR system) based on focused recurrent neural networks (RNNs). In contrast to existing systems, FR system consists of a single end-to-end trainable model for handling all types and senses of discourse relations, requires no feature engineering or external resources, is language-independent, and can be applied at the word and even character levels. At its core, we present our novel generalization of the focused RNNs layer, the first multi-dimensional RNN-attention mechanism for constructing text/argument embeddings. The filtering/gating RNN enables downstream RNNs to focus on different aspects of the input sequence and project it into several embedding subspaces. These argument embeddings are then used to perform sense classification. FR system has been evaluated using the official datasets and methodology of CoNLL 2016 Shared Task. It does not fall a lot behind state-of-the-art performance on English, the most researched and supported language, but it outperforms existing best systems by 2.5% overall results on the Chinese blind dataset. [ABSTRACT FROM AUTHOR]

The abstract of a scientific research article convinces readers that the article deserves to be read. Abstracts can also determine the success of publications and grant applications. In recent years, there has been a trend of cross-disciplinary collaborations in the science community. Scientists have been increasingly expected to engage not only experts of their own disciplines, but also other disciplines with the scope of interest extending to non-experts, such as policy-makers and the general public. Thus, the macro-structure, metadiscoursal and microdiscoursal features exhibited in scientific article abstracts merit attention. In our study, we examined 500 abstracts of scientific research articles published in 50 high-impact journals across five science disciplines (Earth, Formal, Life, Physical and Social Sciences), and performed quantitative analysis of the move structure as well as use of boosters and linguistic features. We found significant interdisciplinary variations in the move structure, boosters and linguistic features employed by these science disciplines. We confirmed that each science discipline possesses a distinct set of macro-structural, metadiscoursal and formalization features, which contribute to its own unique discipline-specific convention. Understanding and observing the disciplinary rhetorical choices and communication conventions will allow scientists to align the abstracts of their studies with the expectations of the targeted audience. [ABSTRACT FROM AUTHOR]

Feature stability, time and tempo of change, and the role of genealogy versus areality in creating linguistic diversity are important issues in current computational research on linguistic typology. This paper presents a database initiative, DiACL Typology, which aims to provide a resource for addressing these questions with specific of the extended Indo-European language area of Eurasia, the region with the best documented linguistic history. The database is pre-prepared for statistical and phylogenetic analyses and contains both linguistic typological data from languages spanning over four millennia, and linguistic metadata concerning geographic location, time period, and reliability of sources. The typological data has been organized according to a hierarchical model of increasing granularity in order to create datasets that are complete and representative. [ABSTRACT FROM AUTHOR]

In this paper the possibility of classification of X-ray images of the cervical vertebrae is studied. The images should be classified into one of the following classes—the images of healthy vertebrae and the images of vertebrae with syndesmophytes. The vertebra contours, described unambiguously by using the generalized shape language, are the basis of the analysis. As a result, the contour is represented as a chain of sinquads that determine switches. The found switches are the characteristic points of the analyzed contour. In these points additional features of the contour are determined. On the basis of these features two aforementioned classes of images are defined as fuzzy sets. Such an approach allows us to create a hierarchical algorithm of classification based on the syntactic and fuzzy description of the contour. [ABSTRACT FROM AUTHOR]

With the development of large-scale knowledge bases (KBs), knowledge-based question answering (KBQA) has become an important research topic in recent years. The key task in KBQA is relation detection, which is the process of finding a compatible answer type for a natural language question and generating its corresponding structured query over a KB. However, existing systems often rely on shallow probabilistic methods, which are less expressive than deep semantic representation methods. In addition, since KBs are still far from complete, it is necessary to develop a new strategy that leverages unstructured resources outside of KBs. In this work, we propose a novel Question Answering method with Relation Detection and Textual Evidence (QARDTE). First, to address the semantic gap problem in relation detection, we use bidirectional long-short term memory networks with different levels of abstraction to better capture sentence structures. Our model achieves improved results with robustness against a wide diversity of expressions and questions with multiple relations. Moreover, to help compensate for the incompleteness of KBs, we utilize external unstructured text to extract additional supporting evidence and combine this evidence with relation information during the answer re-ranking process. In experiments on two well-known benchmarks, our system achieves F1 values of 0.558 (+2.8%) and 0.663 (+5.7%), which are state-of-the-art results that show significant improvement over existing KBQA systems. [ABSTRACT FROM AUTHOR]

Sign languages use the horizontal plane to refer to discourse referents introduced at referential locations. However, the question remains whether the assignment of discourse referents follows a particular default pattern as recently proposed such that two new discourse referents are respectively assigned to the right (ipsilateral) and left (contralateral) side of (right handed) signers. The present event-related potential study on German Sign Language investigates the hypothesis that signers assign distinct and contrastive referential locations to discourse referents even in the absence of overt localization. By using a semantic mismatch-design, we constructed sentence sets where the second sentence was either consistent or inconsistent with the used pronoun. Semantic mismatch conditions evoked an N400, whereas a contralateral sign engendered a Phonological Mismatch Negativity. The current study provides supporting evidence that signers are sensitive to the mismatch and make use of a default pattern to assign distinct and contrastive referential locations to discourse referents. [ABSTRACT FROM AUTHOR]

Scientific writing, particularly quantitative writing, is difficult to master. To help undergraduate students write more clearly about data, we sought to deconstruct writing into discrete, specific elements. We focused on statements typically used to describe data found in the results sections of research articles (quantitative comparative statements, QC). In this paper, we define the essential components of a QC statement and the rules that govern those components. Clearly defined rules allowed us to quantify writing quality of QC statements (4C scoring). Using 4C scoring, we measured student writing gains in a post-test at the end of the term compared to a pre-test (37% improvement). In addition to overall score, 4C scoring provided insight into common writing mistakes by measuring presence/absence of each essential component. Student writing quality in lab reports improved when they practiced writing isolated QC statements. Although we observed a significant increase in writing quality in lab reports describing a simple experiment, we noted a decrease in writing quality when the complexity of the experimental system increased. Our data suggest a negative correlation of writing quality with complexity. We discuss how our data aligns with existing cognitive theories of writing and how science instructors might improve the scientific writing of their students. [ABSTRACT FROM AUTHOR]

Human language contains regular syntactic structures and grammatical patterns that should be detectable in their co-occurence networks. However, most standard complex network measures can hardly differentiate between co-occurence networks built from an empirical corpus and a body of scrambled text. In this work, we employ a motif extraction procedure to show that empirical networks have much greater motif densities. We demonstrate that motifs function as efficient and effective shortcuts in language networks, potentially explaining why we are able to generate and decipher language expressions so rapidly. Finally we suggest a link between motifs and constructions in Construction Grammar as well as speculate on the mechanisms behind the emergence of constructions in the early stages of language acquisition. [ABSTRACT FROM AUTHOR]

The current study used a minimalist paradigm to examine young children’s capacity to imagine and prepare for certain and uncertain immediate future outcomes. In a counterbalanced order, 2.5-year-old children (N = 32) completed twelve trials each of two tasks: (1) the forked tube task, which assessed their ability to cover two possible tube exits to ensure they would catch a single target with an uncertain future trajectory, and (2) the double tube task, which assessed their ability to cover two separate tube exits to ensure they would catch two targets with certain future trajectories. Even though the optimal preparatory action was the same across both tasks, children were much more likely to spontaneously and consistently demonstrate this action in the double tube task than the forked tube task. Children’s responses were unaffected by the number of targets seen in the demonstration phase, and instead appeared to be based on the particular contingencies of each apparatus. These results are consistent with the possibility that young children specifically struggle to imagine and prepare for mutually exclusive versions of uncertain future events. [ABSTRACT FROM AUTHOR]

While mastering a musical instrument takes years, becoming familiar with a new music system requires less time and skills. In this study, we examine whether musically untrained Western listeners can incidentally learn an unfamiliar, microtonal musical scale from simply engaging in a timbre discrimination task. The experiment is comprised of an Exposure and a Test phase. During Exposure, 21 non-musicians were instructed to detect a timbre shift (TS) within short microtonal melodies, and we hypothesised that they would incidentally learn about the pitch interval structure of the microtonal scale from attending to the melodies during the task. In a follow-up Test phase, the tone before the TS was either a member (congruent) or a non-member (incongruent) of the scale. Based on our statistical manipulation of the stimuli, incongruent tones would be a better predictor of an incoming TS than the congruent tones. We therefore expect a faster response time to the shift after the participants have heard an incongruent tone. Specifically, a faster response time observed after an incongruent tone would imply participants’ ability to differentiate tones from the microtonal and the diatonic scale, and reflect their learning of the microtonal pitch intervals. Results are consistent with our predictions. In investigating the learning of a microtonal scale, our study can offer directions for future research on the perception of computer music and new musical genres. [ABSTRACT FROM AUTHOR]

Application of a phonological rule is often conditioned by prosodic structure, which may create a potential perceptual ambiguity, calling for phonological inferencing. Three eye-tracking experiments were conducted to examine how spoken word recognition may be modulated by the interaction between the prosodically-conditioned rule application and phonological inferencing. The rule examined was post-obstruent tensing (POT) in Korean, which changes a lax consonant into a tense after an obstruent only within a prosodic domain of Accentual Phrase (AP). Results of Experiments 1 and 2 revealed that, upon hearing a derived tense form, listeners indeed recovered its underlying (lax) form. The phonological inferencing effect, however, was observed only in the absence of its tense competitor which was acoustically matched with the auditory input. In Experiment 3, a prosodic cue to an AP boundary (which blocks POT) was created before the target using an F0 cue alone (i.e., without any temporal cues), and the phonological inferencing effect disappeared. This supports the view that phonological inferencing is modulated by listeners’ online computation of prosodic structure (rather than through a low-level temporal normalization). Further analyses of the time course of eye movement suggested that the prosodic modulation effect occurred relatively later in the lexical processing. This implies that speech processing involves segmental processing in conjunction with prosodic structural analysis, and calls for further research on how prosodic information is processed along with segmental information in language-specific vs. universally applicable ways. [ABSTRACT FROM AUTHOR]

Introduction: Postprandial hyperglycemia plays a pivotal role in cardiovascular disease. However, few studies have investigated associations between the severity of coronary artery disease (CAD) and postprandial glucose levels in angina patients without known diabetes before coronary angiography. Methods: Subjects who were admitted for coronary angiography due to angina and were in stable condition after discharge were recruited. A standard 75-g oral glucose tolerance test (OGTT) was performed at outpatient visits approximately 2–4 weeks after hospital discharge, and fasting and post-challenge blood glucose were measured. Twenty-six volunteers in our hospital staff served as the healthy group. CAD severity was graded using the SYNTAX and Jeopardy scoring systems. Results: The subjects in the angina group had a higher body mass index, higher fasting glucose, and higher 2-h postprandial glucose than those in the healthy group. The SYNTAX and Jeopardy scores were significantly associated with 2-h postprandial blood glucose (correlation coefficients = 0.164 and 0.187, respectively) but not with fasting glucose. Linear regression analyses revealed that SYNTAX and Jeopardy scores were independently associated with glucose levels at 120 min after OGTT (SYNTAX 95%CI = 0.003–0.103; Jeopardy score 0.002–0.027) but not with fasting glucose. Conclusion: CAD severity is associated with blood glucose levels after oral glucose challenge in patients without known diabetes before coronary angiography, suggesting that CAD patients should be routinely screened for post-challenge blood glucose. [ABSTRACT FROM AUTHOR]

This study uses a maze navigation task in conjunction with a quasi-scripted, prosodically controlled speech task to examine acoustic and articulatory accommodation in pairs of interacting speakers. The experiment uses a dual electromagnetic articulography set-up to collect synchronized acoustic and articulatory kinematic data from two facing speakers simultaneously. We measure the members of a dyad individually before they interact, while they are interacting in a cooperative task, and again individually after they interact. The design is ideally suited to measure speech convergence, divergence, and persistence effects during and after speaker interaction. This study specifically examines how convergence and divergence effects during a dyadic interaction may be related to prosodically salient positions, such as preceding a phrase boundary. The findings of accommodation in fine-grained prosodic measures illuminate our understanding of how the realization of linguistic phrasal structure is coordinated across interacting speakers. Our findings on individual speaker variability and the time course of accommodation provide novel evidence for accommodation at the level of cognitively specified motor control of individual articulatory gestures. Taken together, these results have implications for understanding the cognitive control of interactional behavior in spoken language communication. [ABSTRACT FROM AUTHOR]