Sprache im 20. Jahrhundert. Gegenwartssprache
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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.
We present the annotation of information structure in the MULI project. To learn more about the information structuring means in prosody, syntax and discourse, theory- independent features were defined for each level. We describe the features and illustrate them on an example sentence. To investigate the interplay of features, the representation has to allow for inspecting all three layers at the same time. This is realised by a stand-off XML mark-up with the word as the basic unit. The theory-neutral XML stand-off annotation allows integrating this resource with other linguistic resources such as the Tiger Treebank for German or the Penn treebank for English.
The goal of the MULI (MUltiLingual Information structure) project is to empirically analyse information structure in German and English newspaper texts. In contrast to other projects in which information structure is annotated and investigated (e.g. in the Prague Dependency Treebank, which mirrors the basic information about the topic-focus articulation of the sentence), we do not annotate theory-biased categories like topic-focus or theme-rheme. Trying to be as theory-independent as possible, we annotate those features which are relevant to information structure and on the basis of which typical patterns, co-occurrences or correlations can be determined. We distinguish between three annotation levels: syntax, discourse and prosody. The data is based on the TIGER Corpus for German and the Penn Treebank for English, since the existing information on part-of-speech and syntactic structure can be re-used for our purposes. The actual annotation of an English example sequence illustrates our choice of categories on each level. Their combination offers the possibility to investigate how information structure is realised and can be interpreted.
We present an XML-based metadata standard for the documentation of speech and multimedia corpora that was developed at the Institute for German Language (IDS) in Mannheim, Germany. The IDS is one of the major institutions providing German speech and language corpora to researchers. These corpora stem from many different sources and were previously documented in a rather heterogeneous fashion using a variety of data models and formats. In order to unify the documentation for existing and future corpora, the IDS- internal Archive for Spoken German collaborated with several projects and developed a set of standardised XML metadata schemas. These XML schemas build on existing internal and external documentation schemas (such as IMDI) and take into account the workflow of speech corpus production. In order to minimise redundancy, separate schemas were designed for projects, speakers, recording sessions, and entire corpora. The resulting schemas are tested in ongoing speech and multi-media projects at the IDS and are regularly revised. They are accompanied by element definitions, guidelines, and examples. In addition, a mapping to IMDI will be provided.
The metadata management system for speech corpora “memasysco” has been developed at the Institut für Deutsche Sprache (IDS) and is applied for the first time to document the speech corpus “German Today”. memasysco is based on a data model for the documentation of speech corpora and contains two generic XML schemas that drive data capture, XML native database storage, dynamic publishing, and information retrieval. The development of memasysco’s information architecture was mainly based on the ISLE MetaData Initiative (IMDI) guidelines for publishing metadata of linguistic resources. However, since we also have to support the corpus management process in research projects at the IDS, we need a finer atomic granularity for some documentation components as well as more restrictive categories to ensure data integrity. The XML metadata of different speech corpus projects are centrally validated and natively stored in an Oracle XML database. The extension of the system to the management of annotations of audio and video signals (e.g. orthographic and phonetic transcriptions) is planned for the near future.