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When appearance does not match accent: neural correlates of ethnicity-related expectancy violations
(2017)
Most research on ethnicity in neuroscience and social psychology has focused on visual cues. However, accents are central social markers of ethnicity and strongly influence evaluations of others. Here, we examine how varying auditory (vocal accent) and visual (facial appearance) information about others affects neural correlates of ethnicity-related expectancy violations. Participants listened to standard German and Turkish-accented speakers and were subsequently presented with faces whose ethnic appearance was either congruent or incongruent to these voices. We expected that incongruent targets (e.g. German accent/Turkish face) would be paralleled by a more negative N2 event-related brain potential (ERP) component. Results confirmed this, suggesting that incongruence was related to more effortful processing of both Turkish and German target faces. These targets were also subjectively judged as surprising. Additionally, varying lateralization of ERP responses for Turkish and German faces suggests that the underlying neural generators differ, potentially reflecting different emotional reactions to these targets. Behavioral responses showed an effect of violated expectations: German-accented Turkish-looking targets were evaluated as most competent of all targets. We suggest that bringing together neural and behavioral measures of expectancy violations, and using both visual and auditory information, yields a more complete picture of the processes underlying impression formation.
Complex linguistic phenomena, such as Clitic Climbing in Bosnian, Croatian and Serbian, are often described intuitively, only from the perspective of the main tendency. In this paper, we argue that web corpora currently offer the best source of empirical material for studying Clitic Climbing in BCS. They thus allow the most accurate description of this phenomenon, as less frequent constructions can be tracked only in big, well-annotated data sources. We compare the properties of web corpora for BCS with traditional sources and give examples of studies on CC based on web corpora. Furthermore, we discuss problems related to web corpora and suggest some improvements for the future.
Abschreckend beim Deutschlernen ist u. a. die Erkenntnis, dass man so viel beachten muss, um eine kleine Wortgruppe mit einem Adjektiv, einem Nomen und gegebenenfalls einem Artikel richtig bilden zu können. Es reicht nämlich nicht, zu wissen, ob das Adjektiv vor einem maskulinen, einem femininen oder einem neutralen Nomen steht. Auch das Wissen, in welchem Kasus dieses Nomen steht, reicht nicht aus, um die richtige Form des Adjektivs auszuwählen, nein, man muss auch noch berücksichtigen, ob ein Artikel vor dem Adjektiv steht und wenn ja, welcher, denn auch das beeinflusst die Form des Adjektivs.
Verstehen und Motivieren: semantische Fluchtpunkte deutscher und italienischer Lexeme mit -log-
(2017)
In this paper, we discuss to what extent the German-based contact language Unserdeutsch (Rabaul Creole German, cf. Volker 1982) matches the category‘creole language’ from both a socio-historical and structural perspective. As a point of reference, we will use typological criteria that are widely supposed to be typical for creole languages. It is shown that Unserdeutsch fits fairly well into the pattern of an ‘average creole’, as has been suggested by data in the Atlas of Pidgin and Creole Language Structures (Michaelis et al. 2013). This is despite a series of atypical conditions in its development that might lead us to expect a close structural proximity to the lexifier language, i.e. a relatively acrolectal creole. A possible explanation for this striking discrepancy can be found in the primary function of Unserdeutsch as a marker of identity as well as in the linguistic structure of its substrate language Tok Pisin.
Rückblick 2017
(2017)
Unlike traditional text corpora collected from trustworthy sources, the content of web based corpora has to be filtered. This study briefly discusses the impact of web spam on corpus usability and emphasizes the importance of removing computer generated text from web corpora.
The paper also presents a keyword comparison of an unfiltered corpus with the same collection of texts cleaned by a supervised classifier trained using FastText. The classifier was able to recognize 71% of web spam documents similar to the training set but lacked both precision and recall when applied to short texts from another data set.
Sprachwissenschaft geht logozentrisch vor, konzentriert sich also aufs geschriebene und seit einigen Jahrzehnten auch aufs gesprochene Wort. Das ist verständlich und sinnvoll (Schuster, bleib bei deinen Leisten!), setzt sich aber auch Scheuklappen auf und übersieht bedeutsame Erscheinungen am Rande.
This paper reports about current practice in a staged approach to the introduction of NLP principles and techniques for students of information science (IIM) and of international communication and translation (ICT) as part of their curricula. As most of these students are rather not familiar with computer science or, in the case of IIM students, linguistics, we see them as comparable with students of the humanities. We follow a blended learning strategy with lectures, online materials, tutorials, and screencasts. In the first two terms, we focus on linguistics and its formalisation, NLP tools and applications are then introduced from the third term on. The lectures are combined with tutorials and - since the summer term 2017 - with a set of screencasts.
This article describes a series of ongoing efforts at the Stanford Literary Lab to manage a large collection of literary corpora (~40 billion words). This work is marked by a tension between two competing requirements – the corpora need to be merged together into higher-order collections that can be analyzed as units; but, at the same time, it’s also necessary to preserve granular access to the original metadata and relational organization of each individual corpus. We describe a set of data management practices that try to accommodate both of these requirements – Apache Spark is used to index data as Parquet tables on an HPC cluster at Stanford. Crucially, the approach distinguishes between what we call “canonical” and “combined” corpora, a variation on the well-established notion of a “virtual corpus” (Kupietz et al., 2014; Jakubíek et al., 2014; van Uytvanck, 2010).
In conversation, turn-taking is usually fluid, with next speakers taking their turn right after the end of the previous turn. Most, but not all, previous studies show that next speakers start to plan their turn early, if possible already during the incoming turn. The present study makes use of the list-completion paradigm (Barthel et al., 2016), analyzing speech onset latencies and eye-movements of participants in a task-oriented dialogue with a confederate. The measures are used to disentangle the contributions to the timing of turn-taking of early planning of content on the one hand and initiation of articulation as a reaction to the upcoming turn-end on the other hand. Participants named objects visible on their computer screen in response to utterances that did, or did not, contain lexical and prosodic cues to the end of the incoming turn. In the presence of an early lexical cue, participants showed earlier gaze shifts toward the target objects and responded faster than in its absence, whereas the presence of a late intonational cue only led to faster response times and did not affect the timing of participants' eye movements. The results show that with a combination of eye-movement and turn-transition time measures it is possible to tease apart the effects of early planning and response initiation on turn timing. They are consistent with models of turn-taking that assume that next speakers (a) start planning their response as soon as the incoming turn's message can be understood and (b) monitor the incoming turn for cues to turn-completion so as to initiate their response when turn-transition becomes relevant.