Please use this identifier to cite or link to this item: doi:10.22028/D291-25318
Title: Integrating syntactic and prosodic information for the efficient detection of empty categories
Author(s): Batliner, Anton
Feldhaus, Anke
Geißler, Stefan
Kießling, Andreas
Kiss, Tibor
Kompe, Ralf
Nöth, Elmar
Language: English
Year of Publication: 1996
SWD key words: Künstliche Intelligenz
Free key words: artificial intelligence
DDC notations: 004 Computer science, internet
Publikation type: Report
Abstract: We describe a number of experiments that demonstrate the usefulness of prosodic information for a processing module which parses spoken utterances with a feature based grammar employing empty categories. We show that by requiring certain prosodic properties from those positions in the input, where the presence of an empty category has to be hypothesized, a derivation can be accomplished more efficiently. The approach has been implemented in the machine translation project Verbmobil and results in a significant reduction of the workload for the parser.
Link to this record: urn:nbn:de:bsz:291-scidok-53165
Series name: Vm-Report / Verbmobil, Verbundvorhaben, [Deutsches Forschungszentrum für Künstliche Intelligenz]
Series volume: 113
Date of registration: 13-Jun-2013
Faculty: SE - Sonstige Einrichtungen
Department: SE - DFKI Deutsches Forschungszentrum für Künstliche Intelligenz
Collections:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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