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New KARL (Knowledge Acquisition and Representation Language) allows to specify all parts of a problem-solving method (PSM). It is a formal language with a well-defined semantics and thus allows to represent PSMs precisely and unambiguously yet abstracting from implementation detail. In this paper it is shown how the language KARL has been modified and extended to New KARL to better meet the needs for the representation of PSMs. Based on a conceptual structure of PSMs new language primitives are introduced for KARL to specify such a conceptual structure and to support the configuration of methods. An important goal for this extension was to preserve three important properties of KARL: to be (i) a conceptual, (ii) a formal, and (iii) an executable language.
This paper describes EXMARaLDA, a system for computer transcription of spoken discourse developed and used by the SFB "Mehrsprachigkeit" at the university of Hamburg. EXMARaLDA consists of several DTDs for XML coding of transcription data and some input and output tools for these formats. Apart from being a transcription system in its own right, EXMARaLDA also plays the role of a mediator between older existing data formats at the SFB and between these formats and a planned database of multilingual spoken discourse.
In this paper, we investigate the practical applicability of Co-Training for the task of building a classifier for reference resolution. We are concerned with the question if Co-Training can significantly reduce the amount of manual labeling work and still produce a classifier with an acceptable performance.
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 the perceptual quality of a text-to-speech system. In perception experiments using German speech synthesis, two standard duration models (Klatt rules and CART) were tested. The input to these models consisted of a symbolic representation which was 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 representation 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 derive an appropriate phonological symbolic representation in order to improve timing in synthetic speech.
We present a light-weight tool for the annotation of linguistic data on multiple levels. It is based on the simplification of annotations to sets of markables having attributes and standing in certain relations to each other. We describe the main features of the tool, emphasizing its simplicity, customizability and versatility
This paper describes EXMARaLDA, an XML-based framework for the construction, dissemination and analysis of corpora of spoken language transcriptions. Departing from a prototypical example of a “partitur” (musical score) transcription, the EXMARaLDA “single timeline, multiple tiers” data model and format is presented alongside with the EXMARaLDA Partitur-Editor, a tool for inputting and visualizing such data. This is followed by a discussion of the interaction of EXMARaLDA with other frameworks and tools that work with similar data models. Finally, this paper presents an extension of the “single timeline, multiple tiers” data model and describes its application within the EXMARaLDA system.