幅度—带宽联合分析的语音端点鲁棒检测

A Voice Activity Robust Detection with amplitude—bandwidth analysis

针对在低信噪比条件下难以实现语音端点检测,提出了幅度--带宽联合分析的解决方法,自适应地调整各帧噪声功率谱,有针对性地进行谱减;通过削减随机噪声谱峰,达到了抑制噪声的目的。然后采用语音功率谱点与噪声功率谱点之比序列的方差信息量对语音信号进行双门限检测。新算法经过仿真实验,能够有效地区分语音和噪声,可以显著地提高语音识别系统的性能,在不同的低噪声环境条件下具有鲁棒性。该算法计算代价小,实时性好,简单易实现。

A novel method with amplitude--bandwidth analysis is proposed to overcome the dificulty of low SNR speech endpoint detection.By adaptively adjusting the noise power spectrum of each frame, the stochastic peak of noise spectrum is eliminated and the noise is restrained, then double decision thresholds are applied to detect the speech endpoint in the variance information of speech power spectrum and the noise one ratio.Simulation on computer shows that the new algorithm is more efective in distinguishing speech from noise and is more significant in improveing the performance of automatic speech recognition system.It is proved to be robust under various noisy environments.The algorithm is of low computational complexity and is simple in real-time realization.