Speech utterance classification
Ciprian I. Chelba, M. Mahajan, Alex Acero · 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). · 2003
The paper presents a series of experiments on speech utterance classification performed on the ATIS corpus. We compare the performance of n-gram classifiers with that of Naive Bayes and maximum entropy classifiers. The n-gram classifiers have the advantage that one can use a single pass system (concurrent speech recognition and classification) whereas for Naive Bayes or maximum entropy classification we use a two-stage system: speech recognition followed by classification. Substantial relative improvements (up to 55%) in classification accuracy can be obtained using discriminative. training methods that belong to the class of conditional maximum likelihood techniques.