Characteristic Sequence Analysis of Giant Panda Voiceprint

Abstract

By analyzing the voiceprint characteristics of giant panda’s voice, this study proposes a giant panda individual recognition method based on the characteristics of the composite Mel composite frequency cepstral coefficient (CMFCC) and proves that the characteristic sequence of the CMFCC has long-range dependent characteristics. First, the MFCC (Mel composite frequency cepstral coefficient) with a low frequency resolution is obtained by the Mel filter bank; then, the inverse Mel frequency cepstral coefficient (IMFCC) features of giant panda calls are extracted. The CMFCC characteristic sequence of giant panda voice composed of the MFCC and IMFCC improves the resolution of high- and low-frequency resolution characteristics of giant panda voice. Finally, the first-order difference characteristic parameters of the MFCC are integrated to obtain the difference characteristics between frames. Through experiments, the improvement of the system recognition effect is verified, and the recognition accuracy meets the theoretical expectation.