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Narration in the late middle ages seriality and complexity in the epic prose "Loher and Maller"
(2012)
Previous studies have revealed that infants aged 6-10 months are able to use the acoustic correlates of major prosodic boundaries, that is, pitch change, preboundary lengthening, and pause, for the segmentation of the continuous speech signal. Moreover, investigations with American-English- and Dutch-learning infants suggest that processing prosodic boundary markings involves a weighting of these cues. This weighting seems to develop with increasing exposure to the native language and to underlie crosslinguistic variation. In the following, we report the results of four experiments using the headturn preference procedure to explore the perception of prosodic boundary cues in German infants. We presented 8-month-old infants with a sequence of names in two different prosodic groupings, with or without boundary markers. Infants discriminated both sequences when the boundary was marked by all three cues (Experiment 1) and when it was marked by a pitch change and preboundary lengthening in combination (Experiment 2). The presence of a pitch change (Experiment 3) or preboundary lengthening (Experiment 4) as single cues did not lead to a successful discrimination. Our results indicate that pause is not a necessary cue for German infants. Pitch change and preboundary lengthening in combination, but not as single cues, are sufficient. Hence, by 8 months infants only rely on a convergence of boundary markers. Comparisons with adults' performance on the same stimulus materials suggest that the pattern observed with the 8-month-olds is already consistent with that of adults. We discuss our findings with respect to crosslinguistic variation and the development of a language-specific prosodic cue weighting.
If we can model the cognitive and communicative processes underlying speech, we should be able to better predict what a speaker will do. With this idea as inspiration, we examine a number of prosodic and timing features as potential sources of information on what words the speaker is likely to say next. In spontaneous dialog we find that word probabilities do vary with such features. Using perplexity as the metric, the most informative of these included recent speaking rate, volume, and pitch, and time until end of utterance. Using simple combinations of such features to augment trigram language models gave up to a 8.4% perplexity benefit on the Switchboard corpus, and up to a 1.0% relative reduction in word error rate (0.3% absolute) on the Verbmobil II corpus.
Das Herbsttreffen Patholinguistik wird seit 2007 jährlich vom Verband für Patholinguistik e.V. (vpl) durchgeführt. Die Jubiläumsveranstaltung am 19.11.2011 in Potsdam war nicht nur die 5. Auflage der Veranstaltung, sondern auch ein Fest zum 10jährigen Bestehen des Verbandes. Das Thema lautete "Schluck für Schluck: Dysphagietherapie bei Kindern und Erwachsenen". Im vorliegenden Tagungsband finden sich die Artikel der Hauptvorträge sowie die Abstracts der Posterpräsentationen.
The meaning of linguistic connectives has often been characterized in terms of their position in a bipartite (semantic, pragmatic) or a tripartite (content, epistemic, speech act) structure of domains, depending on what kinds of entities are being connected (largely: propositions or speech acts). This paper argues that a more fine-grained analysis can be achieved by directing some more attention to the characterization of the entities being related. We propose an inventory of categories of illocutionary status for labelling the spans that are being connected. On this basis, the distinction between the content and the epistemic domain, in particular, can be made more explicit. Focusing on the group of causal connectives in German, we conducted a corpus annotation study from which we derived distinct pragmatic 'usage profiles' of the most frequent causal connectives. Finally, we offer some suggestions on the role of illocutions in relation-based accounts of discourse structure.
Annotating linguistic data has become a major field of interest, both for supplying the necessary data for machine learning approaches to NLP applications, and as a research issue in its own right. This comprises issues of technical formats, tools, and methodologies of annotation. We provide a brief overview of these notions and then introduce the papers assembled in this special issue.