한국어 음성인식 플랫폼의 설계 Design of a Korean Speech Recognition Platform

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For educational and research purposes, a Korean speech recognition platform is designed. It is based on an object-oriented architecture and can be easily modified so that researchers can readily evaluate the performance of a recognition algorithm of interest. This platform will save development time for many who are interested in speech recognition. The platform includes the following modules: Noise reduction, end-point detection, met-frequency cepstral coefficient (MFCC) and perceptually linear prediction (PLP)-based feature extraction, hidden Markov model (HMM)-based acoustic modeling, n-gram language modeling, n-best search, and Korean language processing. The decoder of the platform can handle both lexical search trees for large vocabulary speech recognition and finite-state networks for small-to-medium vocabulary speech recognition. It performs word-dependent n-best search algorithm with a bigram language model in the first forward search stage and then extracts a word lattice and restores each lattice path with a trigram language model in the second stage.
Publisher
대한음성학회
Issue Date
2004-09
Language
Korean
Citation

말소리, v.0, no.51, pp.151 - 165

ISSN
1226-5276
URI
http://hdl.handle.net/10203/22669
Appears in Collection
EE-Journal Papers(저널논문)
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