Phonemic segmentation for continuous Mandarin speech recognition

Autor:	Chieko Furuichi, Satoshi Imai, Liyou Hu
Rok vydání:	1997
Předmět:	Variation (linguistics) Acoustics and Ultrasonics Relation (database) Spectral envelope Computer science Speech recognition Cepstrum language Value (computer science) Segmentation Mandarin speech recognition Mandarin Chinese language.human_language
Zdroj:	Journal of the Acoustical Society of Japan (E). 18:1-8
ISSN:	2185-3509 0388-2861
DOI:	10.1250/ast.18.1
Popis:	An algorithm is proposed in this paper for phonemic segmentation to improve the performance of a continuous Mandarin speech recognition systems. The coefficient of time variation of spectral envelope and the coefficient of tirrie. variation of zero order cepstrum are extracted using Unbiased Estimation of Log Spectrum (UELS). The parameter curves based on these coefficients are very smooth, therefore, the relation between parameter's maximum values and phoneme boundaries are easy to be found. By these smooth curves, the maximum value can be used as a criterion to delimit phonemes, rather than the threshold that is used in conventional systems, hence it is possible to get precise segmentation results. 300 sentences were used for an experiment, and the results show the system performance is better than traditional methods. The average phoneme-deletion rate is 1.3%, average phonemeinsertion rate is 3%. For evaluation, the segmentation results were used for a phoneme recognition experiment. 95.5% consonants recognition rate and 92.5% vowel recognition rate were obtained. The results show the approach is highly effective.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::15f03a8f6b0d0b27d4a0d3e28b18df45 https://doi.org/10.1250/ast.18.1 Zobrazit plný text záznamu