Please use this identifier to cite or link to this item: doi:10.22028/D291-25316
Title: A continuous speech recognition system using phonotactic constraints
Author(s): Plannerer, Bernd
Ruske, Günther
Language: English
Year of Publication: 1996
SWD key words: Künstliche Intelligenz
Free key words: artificial intelligence
phonotactic constraints
semicontinuous HMMs
seed model generation
Viterbi training
DDC notations: 004 Computer science, internet
Publikation type: Report
Abstract: This paper describes a speaker-independent recognition system for continuous German speech based on semicontinuous Hidden-Markov-Models which produces a phonetic transcription of the spoken sentence. The recognition units are parts of syllables while the output is a phoneme level transcription. During recognition, the phonotactic constraints of German are taken into account by a micro syntax constrained Viterbi algorithm. A maximum likelihood training procedure based on Viterbi training together with a simple but efficient seed model generation algorithm is presented.
Link to this record: urn:nbn:de:bsz:291-scidok-53184
Series name: Vm-Report / Verbmobil, Verbundvorhaben, [Deutsches Forschungszentrum für Künstliche Intelligenz]
Series volume: 123
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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