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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.
We describe a simple and efficient Java object model and application programming interface (API) for (possibly multi-modal) annotated natural language corpora. Corpora are represented as elements like Sentences, Turns, Utterances, Words, Gestures and Markables. The API allows linguists to access corpora in terms of these discourse-level elements, i.e. at a conceptual level they are familiar with, with the flexibility offered by a general purpose programming language. It is also a contribution to corpus standardization efforts because it is based on a straightforward and easily extensible data model which can serve as a target for conversion of different corpus formats.
In recent decades, the investigation of spoken language has become increasingly important in linguistic research. However, the spoken word is a fleeting phenomenon which is difficult to analyse and which requires an elaborate process of examination and appraisal. The Institute for the German Language (Institut für Deutsche Sprache) has the largest collection of recordings of spoken German, the German Speech Archive (Deutsches Spracharchiv [DSAv]). Up to now, the inadequate processing and accessibility of the valuable material held by the DSAv has been regarded as its major shortcoming. A solution to this problem is at hand now that a start has been made with the systematic modernization of the DSAv and, in particular, with the digitalization of its material. In recent years, we have been able to systematically exploit the unique opportunities provided by a new and easier form of access to the spoken language via the recorded sound signal, which can be realized digitally in the computer, and its linkage to the corresponding texts and documentary data. Through the integration of the existing data about the corpora and of the written versions of the texts into an information and full text database and through the linking of these data with the acoustic signal itself, it is now possible for us to construct a data pool which allows a better documentation of the material and provides rapid internal and external access to the sound recordings. Processed in such a way, the material of the German Speech Archive can now be regarded as having been saved for posterity. As a result, entirely new areas of inquiry and entirely new research perspectives have been opened up. This is true both for the work of the Institute itself and for linguistic research in German as a whole.
Online Access Tools for Spoken German: The Resources of the Deutsches Spracharchiv in a Database
(2002)
This paper shows some details of the modernization of the Deutsches Spracharchiv (DSAv). It explores some future possibilities of linguistical documentation and analysis using the Web. The Institut für Deutsche Sprache (IDS) in Mannheim is the central institution for linguistic research in Germany. The DSAv in the IDS is the center for documentation and research of spoken German. These archives include the largest collection of sound recordings of spoken German (dialects and colloquial speech, including e.g. lots of extinct dialects of former German territories in Eastern Europe) - altogether more than 15,000 sound recordings. The lacking clarification and accessibility of this data material has been felt as an essential deficit. The opportunity to edit the sound signal digitally offers a much easier access to spoken language. Through the integration of the already existing information about the corpora and the transcribed texts in an information- and full text databank, as well as the linking of the data with the acoustic signal (alignment), arises a data-pool with considerably better documentation of the materials and a fast direct grasp of the recorded sounds. Thus, the DSAv initiates totally new research questions for the work at the IDS, as well as for linguistics altogether.
In the context of the HyTex project, our goal is to convert a corpus into a hypertext, basing conversion strategies on annotations which explicitly mark up the text-grammatical structures and relations between text segments. Domain-specific knowledge is represented in the form of a knowledge net, using topic maps. We use XML as an interchange format. In this paper, we focus on a declarative rule language designed to express conversion strategies in terms of text-grammatical structures and hypertext results. The strategies can be formulated in a concise formal syntax which is independend of the markup, and which can be transformed automatically into executable program code.
The development of tools for computer-assisted transcription and analysis of extensive speech corpora is one main issue at the Institute of German Language (IDS) and the Institute of Natural Language Processing (IMS). Corpora of natural spoken dialogue have been transcribed, and the analogue recordings of these discourses are digitized. An automatic segmentation system is employed which is based on Hidden Markov Models. The orthographic representation of the speech signal is transformed into a phonetic representation, the phonetic transcription is transformed into a system-internal representation, and the time alignment between text and speech signal follows. In this article, we also describe the retrieval software Cosmas II and its special features for searching discourse transcripts and playing time aligned passages.