语音信号的增强相对谱滤波
An enhanced RASTA filtering of speech
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摘要: 提出了在语音信号对数功率谱域和功率谱域顺序滤波的新的增强RASTA滤波(E_RASTA)方法。语音识别和说话人识别实验表明,E_RASTA滤波能够有效地去除加性噪声和卷积噪声的干扰,E_RASTA算法与语音信号的失真过程和噪声的功率谱无关。E_RASTA方法性能同J_RASTA算法类似或更好,且不需要J_RASTA 算法中的实时语音信噪比估计。E_RASTA 滤波器的设计表明,低频率的谱调制分量可引起语音识别和说话人识别性能的下降,说话人识别较语音识别需要较小的谱时间调制带宽。Abstract: We propose an Enhanced RASTA (ERASTA) technique for speech and speaker recognition. The new method consists of classical RASTA filtering in logarithmic spectrum domain following by another RASTA processing in spectrum domain. In this manner, both the channel distortion and additive noise are removed effectively. In isolated digit speaker identification and speech recognition experiment on TI46 database, we found that the ERASTA performed equal or better than JRASTA method in both tasks. The ERASTA does not need the speech SNR estimation in order to determinate the optimal value of J in JRASTA, and the information of how the speech degrades. The choice of ERASTA filters also indicates that the low frequency modulation components in degraded speech can deteriorate the performance of both recognition tasks. Besides, the speaker speaker needs less temporal modulation frequency band than the speech recognition.