Musical-noise-free noise reduction by using biased harmonic regeneration and considering relationship between a priori SNR and sound quality
Masakazu Une, Ryoichi Miyazaki · Applied Acoustics · 2020
This paper focuses on two representative single-microphone noise reduction problems: speech distortion and musical noise. Many noise reduction methods have been proposed for each problem. Harmonic regeneration noise reduction (HRNR) was introduced for the improvements of speech distortion and the a priori signal-to-noise ratio (SNR) estimator. HRNR involves using a unique signal to regenerate harmonics, which had been eliminated. Musical-noise-free noise reduction based on the minimum-mean square error short-time spectral amplitude estimator (musical-noise-free MMSE-STSA estimator) has also been proposed. This method can suppress a noisy signal without generating musical noise by introducing a bias into the classical a priori SNR estimator. We propose a noise reduction method for addressing these problems simultaneously by improving the classical a priori SNR estimator. We investigated the behavior of the internal parameters for the proposed and conventional methods with regard to speech quality and show the effectiveness of the proposed method in terms of speech distortion and musical noise. We consider and discuss the relationship between the estimation accuracy of an a priori SNR and speech quality. Specifically, we consider the factors to improve speech quality in terms of biasing.