机构:
Univ Bielefeld, Fac Technol, D-33501 Bielefeld, GermanyUniv Bielefeld, Fac Technol, D-33501 Bielefeld, Germany
Fink, GA
[1
]
机构:
[1] Univ Bielefeld, Fac Technol, D-33501 Bielefeld, Germany
来源:
TEXT, SPEECH AND DIALOGUE
|
1999年
/
1692卷
关键词:
D O I:
暂无
中图分类号:
TP18 [人工智能理论];
学科分类号:
081104 ;
0812 ;
0835 ;
1405 ;
摘要:
ESMERALDA is an integrated environment for the development of speech recognition systems. It provides a powerful selection of methods for building statistical models together with an efficient incremental recognizer. In this paper the approaches adopted for estimating mixture densities, Hidden Markov Models, and n-gram language models are described as well as the algorithms applied during recognition. Evaluation results on a speaker independent spontaneous speech recognition task demonstrate the capabilities of ESMERALDA.