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Predictor codebook for speaker-independent speech recognition

This paper discusses a method to handle the diversified dynamic features of speech by representing the dynamic features of speech by spectrum predictors and constructing the codebook containing predictors as the elements. The effectiveness of the method for speaker-independent speech recognition is examined. Three kinds of predictor structures, i.e., the forward predictor, the backward predictor and the interpolator, are examined. The predictor codebook is constructed by the predictor quantization procedure, which is a small modification of the LBG algorithm. For the evaluation of the phoneme recognition level, two kinds statistical evaluation quantities and the phoneme recognition rate have been considered. It is seen as a result that the predictor codebook can realize a high phoneme separation capability and the robustness against the speaker variation. By combining the process actually into the phrase recognition system, the performance at the continuous speech recognition level is evaluated. In either case, the codebook with the backward predictor as the elements exhibited the highest performance.