An Automatic Speech Translation System on PDAs for Travel Conversation
ICMI '02 Proceedings of the 4th IEEE International Conference on Multimodal Interfaces
Linear discriminant analysis for improved large vocabulary continuous speech recognition
ICASSP'92 Proceedings of the 1992 IEEE international conference on Acoustics, speech and signal processing - Volume 1
Exploiting prediction error in a predictive-based connectionist speech recognition system
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: speech processing - Volume II
| Hi-index | 0.00 |
The authors present a method for improving HMM (hidden Markov model) phonetic discrimination capability which is a linear discriminant transform of acoustic features to a continuous-valued feature space such that phonetic distinctions correlate closely with Euclidean distance in the transformed feature space. Experimental testing with a 30-word single syllable highly confusable vocabulary showed that the acoustic-phonetic transform could be used to reduce word error rates approximately 25%. In general, results based on the LDA2 transform, i.e., linear discriminant analysis with whitening of the within-class covariance matrices, are superior to those obtained with LDA1, linear discriminant analysis without whitening. Recognition results also improve if a block transform of several frames per block is used rather than a transform based on one frame per block.