A two pass classifier for utterance rejection in keyword spotting
- 1 January 1993
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- Vol. 2 (15206149) , 451-454 vol.2
- https://doi.org/10.1109/icassp.1993.319338
Abstract
A classifier for utterance rejection in a hidden Markov model (HMM) based speech recognizer is presented. This classifier, termed the two-pass classifier, is a postprocessor to the HMM recognizer, and consists of a two-stage discriminant analysis. The first stage employs the generalized probabilistic descent (GPD) discriminative training framework, while the second stage performs linear discrimination combining the output of the first stage with HMM likelihood scores. In this fashion the classification power of the HMM is combined with that of the GPD stage which is specifically designed for keyword/nonkeyword classification. Experimental results show that, on two separate databases, the two-pass classifier significantly outperforms a single-pass classifier based solely on the HMM likelihood scores.Keywords
This publication has 7 references indexed in Scilit:
- A study of speech recognition for children and the elderlyPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- A hidden Markov model based keyword recognition systemPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2002
- Speech recognition using segmental neural netsPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1992
- Segmental GPD training of HMM based speech recognizerPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1992
- Discriminative analysis for feature reduction in automatic speech recognitionPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1992
- A new connected word recognition algorithm based on HMM/LVQ segmentation and LVQ classificationPublished by Institute of Electrical and Electronics Engineers (IEEE) ,1991
- Automatic recognition of keywords in unconstrained speech using hidden Markov modelsIEEE Transactions on Acoustics, Speech, and Signal Processing, 1990