Die Conodontendiagnese als Inkohlungsparameter und ein Vergleich unterschiedlich sensitiver Diageneseindikatoren am Beispiel von Triassedimenten Nord- und Mitteldeutschlands

SIGLEAvailable from TIB Hannover: RO 786(37) / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekDEGerman

A frame and segment based approach for topic spotting

In this paper we present a new approach for topic spotting based on subword units (phonemes and feature vectors) instead of words. Classification of topics is done by running topic dependent polygram language models over these symbol sequences and deciding for the one with the best score. We trained and tested the two methods on three different corpora. The first is a part of a media corpus which contains data from TV shows for three different topics (IDS), the second is part of the Switchboard corpus, the third is a collection of human machine dialogs about train timetable information (EVAR corpus). The results on Switchboard are compared with phoneme based approaches which were made at CRIM (Montreal) and DRA (Malvern) and are presented as ROC curves; the results on IDS and EVAR are compared with a word based approach and presented as confusion tables. We show that a surprisingly little amount of recognition accuracy is lost when going from word to subword based topic spotting. (orig.)Appeared in proceedings EUROSPEECH '97, Rhodes (ZA), vol. 1, p. 275-278Available from TIB Hannover: RR 5221(217)+a / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekSIGLEBundesministerium fuer Bildung, Wissenschaft, Forschung und Technologie, Bonn (Germany)DEGerman

SQEL: A Multilingual and Multifunctional Dialogue System

Within the EC-funded project SQEL, the German EVAR spoken dialogue system has been extended with respect to multilinguality and multifunctionality. The current demonstrator can handle four different languages and domains: German, Slovak, and Czech (and their national train connections), and Slovenian (European flights). The SQEL demonstrator can also access databases on the WWW, which enables users without an internet connection to meet their information needs by just using the phone. The system starts up with a German opening phrase and the user is free to use any of the implemented languages. Amultilingual word recognizer implicitly identifies the language, which is then associated with the appropriate domain and database. For the remainder of the dialogue, the corresponding monolingual recognizer is used instead. Experiments to date have shown that the multilingual and the (respective) monolingual recognizers attain comparable word accuracy rates, although the former is less efficient. The existence of language-independent task parameters, such as goal and source location, has meant that porting the system to a new language involves mainly the development of lexica and grammars (apart from the word recognizers) and not an extensive restructuring of the interpretation process within the Dialogue Manager. The latter is sufficiently flexible to switchbetween the different domains and languages

Topic spotting using subword units

In this paper we present a new approach for topic spotting based on subword units and feature vectors instead of words. In our first approach, we only use vector quantized feature vectors and polygram language models for topic representation. In the second approach, we use phonemes instead of the vector quantized feature vectors and model the topics again using polygram language models. We trained and tested the two methods on two different corpora. The first is a part of a media corpus which contains data form TV shows for three different topics. The second is the Verbmobil-corpus where we used 18 dialog acts as topics. Each corpus was splitted into disjunctive test and training sets. We achieved recognition rates up to 82% for the three topics of the media corpus and up to 64% using 18 dialog acts of the Verbmobil-corpus as topics. (orig.)SIGLEAvailable from TIB Hannover: RR 5221(205)+a / FIZ - Fachinformationszzentrum Karlsruhe / TIB - Technische InformationsbibliothekBundesministerium fuer Bildung, Wissenschaft, Forschung und Technologie, Bonn (Germany)DEGerman