Comparative study of several distortion measures for speech recognition

In this study we compared several different spectral distortion measures including the Itakura-Saito (IS), the log likelihood ratio (LLR), the likelihood ratio (LR), the cepstral (CEP), and two perceptually based distortion measures, the weighted likelihood ratio (WLR) and the weighted slope metric (WSM) distortion measures, in terms of their effects on the performance of a standard dynamic time warping (DTW) based, isolated word, speech recognizer. Two modifications of the basic forms of each measure were also investigated, namely a Bark-scale frequency warping and the incorporation of suprasegmental energy information. All distortion measures and their modifications were tested on an alpha-digit vocabulary, 4-talker, telephone recording data base. The results can be summarized as: (1) All LPC-based distortion measures performed reasonably well. The LLR and WSM distortion measures gave the highest recognition accuracy, while the IS distortion measure gave the lowest score; (2) Whereas the addition of suprasegmental energy information helped the recognition performance, the use of gain and absolute loudness degraded the performance; (3) Bark-scale frequency warping did not perform as well as its unwarped counterpart; (4) The WLR distortion measure did not perform as well as its unweighted counterpart.