Spectral movement function and its application to speech recognition

The authors propose a new mathematical method for extracting spectral movement in a time-sequence of speech spectrum. The spectral movement is characterized by the time and frequency derivative of a time-sequence of log spectrum envelopes. Spectral movement direction, the movement toward a higher or lower frequency region, can be identified by the sign of the proposed function. A parameter which can be used for speech segmentation is derived form this function A distance measure for speech recognition is also derived as the Euclidean distance between two spectral movement patterns extracted by the proposed function. This distance is easily calculated using cepstrum coefficients. Speech recognition results using dynamic time warping template matching with this new distance measure indicate that recognition error rate can be reduced to less than half compared with the conventional Euclidean cepstrum distance measure