Frequency weighted LPC spectral matching measures

Spectral matching is a powerful method of calculating the distance between two frames in speech data which is used in speech analysis, speech recognition and the evaluation of speech quality. Since the introduction of LPC [linear prediction coefficient] analysis, several LPC spectral matching measures have been proposed. It is widely known that human hearing has greater sensitivity in the low‐frequency region than in the high‐frequency region. However, it is impossible to assign frequency weighting using conventional LPC spectral matching measures. This paper proposes two types of frequency weighted LPC spectral matching. The first method is applicable only to the peak weighted measure, while the second is applicable to a more general LPC spectral matching measure. The theoretical relation between these two types of frequency weighting methods is discussed and vowel identification experiments are carried out to examine the effectiveness of these methods. It is seen that the first method is effective in assigning the same frequency weighting to all frames and the second method is effective in assigning different frequency weightings to frames with different phonemic reference patterns.