PHMM BASED ASYNCHRONOUS ACOUSTIC MODEL FOR CHINESE LARGE VOCABULARY CONTINUOUS SPEECH RECOGNITION
被引:0
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作者:
Wu, Hao
论文数: 0引用数: 0
h-index: 0
机构:
Peking Univ, Minist Educ, Key Lab Machine Percept, Hearing Res Ctr, Beijing 100871, Peoples R ChinaPeking Univ, Minist Educ, Key Lab Machine Percept, Hearing Res Ctr, Beijing 100871, Peoples R China
Wu, Hao
[1
]
Wu, Xihong
论文数: 0引用数: 0
h-index: 0
机构:
Peking Univ, Minist Educ, Key Lab Machine Percept, Hearing Res Ctr, Beijing 100871, Peoples R ChinaPeking Univ, Minist Educ, Key Lab Machine Percept, Hearing Res Ctr, Beijing 100871, Peoples R China
Wu, Xihong
[1
]
Chi, Huisheng
论文数: 0引用数: 0
h-index: 0
机构:
Peking Univ, Minist Educ, Key Lab Machine Percept, Hearing Res Ctr, Beijing 100871, Peoples R ChinaPeking Univ, Minist Educ, Key Lab Machine Percept, Hearing Res Ctr, Beijing 100871, Peoples R China
Chi, Huisheng
[1
]
机构:
[1] Peking Univ, Minist Educ, Key Lab Machine Percept, Hearing Res Ctr, Beijing 100871, Peoples R China
来源:
2009 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS 1- 8, PROCEEDINGS
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2009年
关键词:
tonal language;
multiple stream;
PHMM;
D O I:
暂无
中图分类号:
O42 [声学];
学科分类号:
070206 ;
082403 ;
摘要:
In this paper, we presented an asynchronous multiple stream based Chinese tonal acoustic modeling framework. In this framework, toneless phonetic units and tones are modeled separately with different acoustic features. During the training, and decoding process, a set of models are coupled together with a product hidden Markov models (PHMM) to represent whole tonal phonetic units. Through this, a compound context dependent tonal model can be generated from a few simple models. Experiments show that such model scheme generates more compact and accurate model presentation and brings improvement on the performance for large vocabulary speech recognition tasks.