关键词: 信息处理技术, 端点检测, 循环平均幅度差函数, Teager能量, 基本谱熵, 噪声环境

Abstract: In order to solve the problem of speech endpoint detection in realworld noisy environments, a new robust feature extraction technique for speech endpoint detection was proposed. In the technique, the cyclic average magnitude difference function in the fundemental tone detection in combination with the basic spectral entropy was applied to extract the features of speech endpoint. The proposed technique is characterized by adaptation to the various noisy environments without any need for a prior knowledge of the noise. Simulation results show that the feature extraction is effective to reduce the impact of various kinds of noise under low signaltonoise ratio.

Key words: information processing technology, endpoint detection, circular average magnitude difference function, Teager energy, basic spectral entropy, noisy environment