基于扩展谱相减的RCAF基音周期检测算法

RCAF Pitch Detection Algorithm Based on Expanded Spectral Subtraction

针对传统基音检测算法在信噪比低的情况下提取的基音周期错误率较高,该文提出了一种基于RCAF(Reverse CAMDF Autocorrelation Function)搜索试探平滑的基音轨迹提取方法。采用自适应判决准则的扩展谱相减进行语音增强,在语音段实现了对噪声信号的估计。应用RCAF算法提取基音周期,通过搜索试探平滑算法对提取出的基音周期进行平滑处理。该算法降低了误判率,提高了提取精度。仿真结果表明,该算法在-10dB信噪比情况下,其性能优于传统的CAMDF和AWAC等方法。

A new pitch detection of noisy speech signal for lower SNR is proposed in this paper, which is based on Reverse CAMDF Autocorrelation Function （RCAF） and searching tentative smooth measurement. The algorithm can estimate noise during speech presence, which employs the method of expanded spectral subtraction based on noise compensation structure. RCAF algorithm improves the robustness and precision of pitch detection. A number of experiments show that by RCAF method, higher efficiency and better detection accuracy can be ob- tained while the SNR is equal to -10dB. However, such performance can not be achieved by traditional methods, AMDF, CAMDF and AWAC under the same SNR.