Title
A confidence measure based on agreement among multiple LVCSR models - correlation between pair of acoustic models and confidence
Abstract
For many practical applications of speech recognition systems, it is quite desirable to have an estimate of confidence for each hypoth- esized word. Unlike previous works on confidence measures, this paper studies features for confidence measures that are extracted from outputs of more than oneLVCSR models. More specifically, this paper experimentally evaluates the agreement among the out- puts of multiple Japanese LVCSR models, with respect to whether it is effective as an estimate of confidence for each hypothesized word. The results of experimental evaluation show that the agree- ment between the outputs with two LVCSR models with differ- ent decoders and acoustic models can achieve quite reliable con- fidence. Furthermore, among various features of acoustic models based on Gaussian mixture HMMs, it is concluded that ones such as whether or not to have short pause models, as well as different units in HMMs (e.g., triphone model or syllable model) are the most effective in achieving highly reliable confidence.
Year
Venue
Keywords
2002
INTERSPEECH
speech recognition
Field
DocType
Citations 
Triphone,Weighting,Pattern recognition,Computer science,Trigram,Speech recognition,Gaussian,Dictation,Syllable,Artificial intelligence,Decoding methods,Hidden Markov model
Conference
4
PageRank 
References 
Authors
0.52
7
4
Name
Order
Citations
PageRank
takehito utsuro145682.76
Tetsuji Harada251.21
Hiromitsu Nishizaki316329.49
Seiichi Nakagawa4598104.03