원문정보
초록
영어
Noise power spectral density (PSD) estimation is a crucial part of speech enhancement system due to its contributory effect on the quality of the noise reduced speech. A novel estimation method for color noise PSD on the basis of an assumption of generalized Gamma distribution and maximum a posteriori (MAP) criterion is proposed. In the experiment, generalized Gamma PDF which is a natural extension of the Gaussian modeling of a non-white components distribution is found best fitting in four types of color noises compared with Laplace, Rayleigh distributions. After that MAP noise estimators based on the reported generalized Gamma PDF models are competed with Minimum Statistics (MS), minimum mean square error (MMSE) based PSD estimation and Maximum Likelihood estimation (MLE) noise tracking methods in evaluations. The performance of the proposed noise estimations are good as demonstrated by log error, segmental SNR and PESQ measures when they are integrated with the speech enhancement technique.
목차
1. Introduction
2. Noise Magnitude Models and Statistical Analysis
2.1. The Distribution of Noise Spectral Amplitude
2.2. The Approximate Generalized Gamma PDF
2.3. The Parameters of the Normalized Approximate Probability Density Function
2.5. Noise PSD Estimation based on MAP
3. Experiments and Simulated Results
3.1. Modified Wiener Filter
3.2. Experiment Setup
3.3. Evaluation Measures
3.4. Performance Evaluation
4. Conclusions
References