Bitte benutzen Sie diese Referenz, um auf diese Ressource zu verweisen: doi:10.22028/D291-25330
Titel: Improving parsing of spontaneous speech with the help of prosodic boundaries
Verfasser: Kompe, Ralf
Kießling, Andreas
Niemann, Heinrich
Nöth, Elmar
Batliner, Anton
Schacht, S.
Ruland, T.
Block, H. U.
Sprache: Englisch
Erscheinungsjahr: 1997
SWD-Schlagwörter: Künstliche Intelligenz
Freie Schlagwörter: artificial intelligence
DDC-Sachgruppe: 004 Informatik
Dokumentart : Report (Bericht)
Kurzfassung: Parsing can be improved in automatic speech understanding if prosodic boundary marking is taken into account, because syntactic boundaries are often marked by prosodic means. Because large databases are needed for the training of statistical models for prosodic boundaries, we developed a labeling scheme for syntactic-prosodic boundaries within the German VERBMOBIL project (automatic speech-to-speech translation). We compare the results of classifiers (multi-layer perceptrons and language models) trained on these syntactic-prosodic boundary labels with classifiers trained on perceptual-prosodic and purely syntactic labels. Recognition rates of up to 96% were achieved. The turns that we need to parse consist of 20 words on the average and frequently contain sequences of partial sentence equivalents due to restarts, ellipsis, etc. For this material, the boundary scores computed by our classifiers can successfully be integrated into the syntactic parsing of word graphs; currently, they improve the parse time by 92% and reduce the number of parse trees by 96%. This is achieved by introducing a special Prosodic Syntactic Clause Boundary symbol (PSCB) into our grammar and guiding the search for the best word chain with the prosodic boundary scores.
Link zu diesem Datensatz: urn:nbn:de:bsz:291-scidok-54848
Schriftenreihe: Vm-Report / Verbmobil, Verbundvorhaben, [Deutsches Forschungszentrum für Künstliche Intelligenz]
Band: 210
SciDok-Publikation: 10-Sep-2013
Fakultät: Sonstige Einrichtungen
Fachrichtung: SE - DFKI Deutsches Forschungszentrum für Künstliche Intelligenz
Fakultät / Institution:SE - Sonstige Einrichtungen

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