Context-Dependent Word Duration Modeling for Korean Connected Digit Recognition

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In a Korean connected digit recogniser, duration modelling is necessary to reduce insertion and deletion errors due to monophonemic digits, which cannot usually be corrected even by discriminative training algorithms. In the Latter the authors incorporate context-dependent word duration modelling directly in a decoding algorithm to reduce those errors. While incorporating duration information in the postprocessing stage shows little improvements over a baseline system, the proposed method reduces word error rates by similar to 10% for unknown length decoding when both maximum likelihood estimation and generalised probabilistic descent training are used.
Publisher
Inst Engineering Technology-Iet
Issue Date
1995-09
Language
English
Article Type
Article
Keywords

HIDDEN MARKOV-MODELS

Citation

ELECTRONICS LETTERS, v.31, no.19, pp.1630 - 1631

ISSN
0013-5194
URI
http://hdl.handle.net/10203/70168
Appears in Collection
EE-Journal Papers(저널논문)
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