Robust noise power spectral density estimation for binaural speech enhancement in time-varying diffuse noise field
| Autor: | Young-Cheol Park, Youna Ji, Yonghyun Baek |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
Noise power
Acoustics and Ultrasonics Computer science Acoustics Diffuse noise field ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION lcsh:QC221-246 02 engineering and technology lcsh:QA75.5-76.95 030507 speech-language pathology & audiology 03 medical and health sciences symbols.namesake Phase noise Binaural speech enhancement 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering Noise measurement Noise spectral density 020206 networking & telecommunications Noise floor Noise PSD estimation Speech enhancement Gaussian noise Colors of noise lcsh:Acoustics. Sound symbols lcsh:Electronic computers. Computer science 0305 other medical science Algorithm |
| Zdroj: | EURASIP Journal on Audio, Speech, and Music Processing, Vol 2017, Iss 1, Pp 1-16 (2017) |
| ISSN: | 1687-4722 |
| DOI: | 10.1186/s13636-017-0122-4 |
| Popis: | In speech enhancement, noise power spectral density (PSD) estimation plays a key role in determining appropriate de-nosing gains. In this paper, we propose a robust noise PSD estimator for binaural speech enhancement in time-varying noise environments. First, it is shown that the noise PSD can be numerically obtained using an eigenvalue of the input covariance matrix. A simplified estimator is then derived through an approximation process, so that the noise PSD is expressed as a combination of the second eigenvalue of the input covariance matrix, the noise coherence, and the interaural phase difference (IPD) of the input signal. Later, to enhance the accuracy of the noise PSD estimate in time-varying noise environments, an eigenvalue compensation scheme is presented, in which two eigenvalues obtained in noise-dominant regions are combined using a weighting parameter based on the speech presence probability (SPP). Compared with the previous prediction filter-based approach, the proposed method requires neither causality delays nor explicit estimation of the prediction errors. Finally, the proposed noise PSD estimator is applied to a binaural speech enhancement system, and its performance is evaluated through computer simulations. The simulation results show that the proposed noise PSD estimator yields accurate noise PSD regardless of the direction of the target speech signal. Therefore, slightly better performance in quality and intelligibility can be obtained than that with conventional algorithms. |
| Databáze: | OpenAIRE |
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