DocumentCode :
2263030
Title :
Syllable-level desynchronisation of phonetic features for speech recognition
Author :
Kirchhoff, Katrin
Author_Institution :
Tech. Fakultat, Bielefeld Univ., Germany
Volume :
4
fYear :
1996
fDate :
3-6 Oct 1996
Firstpage :
2274
Abstract :
Describes a novel approach to speech recognition which is based on phonetic features as basic recognition units and the delayed synchronisation of these features within a higher-level prosodic domain, viz. the syllable. The object of this approach is to avoid a rigid segmentation of the speech signal as it is usually carried out by standard segment-based recognition systems. The architectural setup of the system is described, as well as evaluation tests carried out on a medium-sized corpus of spontaneous speech (German). Syllable and phoneme recognition results are given and compared to recognition rates obtained by a standard triphone-based HMM recogniser trained and tested on the same data set
Keywords :
hidden Markov models; speech recognition; synchronisation; German spontaneous speech corpus; architectural setup; delayed synchronisation; evaluation tests; hidden Markov method; high-level prosodic domain; phoneme recognition; phonetic features; recognition rates; segment-based recognition systems; speech recognition; speech signal segmentation; syllable recognition; syllable-level desynchronisation; training; triphone-based HMM recogniser; Acoustic testing; Computer vision; Context modeling; Delay; Hidden Markov models; Speech recognition; Stochastic processes; System testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Spoken Language, 1996. ICSLP 96. Proceedings., Fourth International Conference on
Conference_Location :
Philadelphia, PA
Print_ISBN :
0-7803-3555-4
Type :
conf
DOI :
10.1109/ICSLP.1996.607260
Filename :
607260
Link To Document :
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