Musical-noise-free blind speech extraction using ICA-based noise estimation and iterative spectral subtraction
Ryoichi Miyazaki, Hiroshi Saruwatari, Kiyohiro Shikano, Kazunobu Kondo · 2012
In this paper, we propose a new iterative signal extraction method using a microphone array that can be applied to nonstationary noise. In our previous study, it was found that optimized iterative spectral subtraction (SS) results in speech enhancement with almost no musical noise generation, but this method is valid only for stationary noise. The proposed method consists of iterative blind dynamic noise estimation by independent component analysis (ICA) and musical-noise-free speech extraction by modified iterative SS, where multiple iterative SS is applied to each channel while maintaining the multi-channel property reused for ICA. Also, related to the proposed method, we discuss the justification of applying ICA to such signals nonlinearly distorted by SS. From objective and subjective evaluations, we reveal that the proposed method outperforms the conventional method.