Sprache im 20. Jahrhundert. Gegenwartssprache
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Der Kurzbeitrag berichtet über ein Projekt ”Hypertextualisierung auf textgrammatischer Grundlage“ (HyTex), in dem erforscht wird, wie sich linear organisierte Dokumente mit semiautomatischen Methoden auf der Grundlage von textgrammatischem Markup und der linguistisch motivierten Modellierung terminologischen Wissens in delinearisierte Hyperdokumente überführen lassen. Ziel ist es, eine Sammlung von Fachtexten so in einen Hypertext zu überführen, dass terminologiebedingte Verständnisschwierigkeiten beim Lesen durch entsprechende Linkangebote aufgelöst werden, so dass die Fachtexte auch von Semi-Experten der Domäne selektiv gelesen werden können. Der Schwerpunkt des Beitrags liegt auf der Modellierung terminologischen Wissens mit XML Topic Maps und dessen Stellenwert für die automatische Erzeugung von Hyperlinks.
Both for psychology and linguistics, emotion concepts are a continuing challenge for analysis in several respects. In this contribution, we take up the language of emotion as an object of study from several angles. First, we consider how frame semantic analyses of this domain by the FrameNet project have been developing over time, due to theory-internal as well as application-oriented goals, towards ever more fine-grained distinctions and greater within-frame consistency. Second, we compare how FrameNet’s linguistically oriented analysis of lexical items in the emotion domain compares to the analysis by domain experts of the experiences that give rise (directly or indirectly) to the lexical items. And finally, we consider to what extent frame semantic analysis can capture phenomena such as connotation and inference about attitudes, which are important in the field of sentiment analysis and opinion mining, even if they do not involve the direct evocation of emotion.
This paper explores on the basis of empirical research, how patterns of interaction and argumentation in political discourse on Twitter evolve as translocal communities in the creative shape of “joint digital storytelling”. Joint storytelling embraces coordinated activities by multiple actors focusing on a shared topic. By adding personal information and evaluation, participants construct an open narrative format, which can be inviting and inspiring for others, who then join in with their own narratives. This model will be exemplified by analyzing a large amount of tweets (107,000) collected during a political conflict between proponents and adversaries of a local traffic project in Germany. Analysis is based on (1) the textual level, (2) the operative level (hashtags, @- and RT-Symbol, hyperlinks etc.) and (3) the visual level of storytelling (embedded photos, videos). Results show a new way of creating translocal online communities and political deliberation.
In order to determine priorities for the improvement of timing in synthetic speech this study looks at the role of segmental duration prediction and the role of phonological symbolic representation in listeners' preferences. In perception experiments using German speech synthesis, two standard duration models (Klatt rules and CART) were tested. The input to these models consisted of symbolic strings which were either derived from a database or a text-to-speech system. Results of the perception experiments show that different duration models can only be distinguished when the symbolic string is appropriate. Considering the relative importance of the symbolic representation, "post-lexical" segmental rules were investigated with the outcome that listeners differ in their preferences regarding the degree of segmental reduction. As a conclusion, before fine-tuning the duration prediction, it is important to calculate an appropriate phonological symbolic representation in order to improve timing in synthetic speech.
In this study we investigate the intonational characteristics of the four utterance types statement, wh-question, yes/no-question and declarative question. Readings of two German scripted dialogues were examined to ascertain characteristic features of the F0 contour for each utterance type. Final boundary tone, nuclear pitch accent, F0 offset, F0 onset, F0 range, and the slopes of a topline and a bottomline were determined for each utterance and compared for the four utterance types. Results show that for an average speaker, the final boundary tone, the F0 range, and the slope of the topline can be used to distinguish between the four utterance types. However, speakers may deviate from this pattern and exploit other intonational means to distinguish certain utterance types or choose not to mark a syntactic difference at all.
The naturalness of synthetic speech depends strongly on the prediction of appropriate prosody. For the present study the original annotation of the German speech database “Kiel Corpus of Read Speech” was extended automatically with syntactic features, word frequency, and syllable boundaries. Several classification and regression trees for predicting symbolic prosody features, postlexical phonological processes, duration, and F0 were trained on this database. The perceptual evaluation showed that the overall perceptual quality of the German text-to-speech system MARY can be significantly improved by training all models that contribute to prosody prediction on the same database. Furthermore, it showed that the error introduced by symbolic prosody prediction perceptually equals the error produced by a direct method that does not exploit any symbolic prosody features.