Speech Signal Processing
|Title||Estimation of the Noise Correlation Matrix |
|Authors||Richard C. Hendriks, Timo Gerkmann |
|Conference||Int. Conf. Acoustics, Speech, Signal Processing (ICASSP) |
|Place ||Prague, Czech Republic |
To harvest the potential of multi-channel noise reduction methods, it is crucial to have an accurate estimate of the noise correlation matrix. Existing algorithms either assume speech absence and exploit a voice activity detector (VAD), or make use of additional assumptions like a diffuse noise field. Therefore, these algorithms are limited with respect to their tracking speed and the type of noise fields for which they can estimate the correlation matrix.
In this paper we present a new method for noise correlation matrix estimation that makes no assumptions about the type of noise field, nor uses a VAD. The presented method exploits the existence of accurate single-channel noise PSD estimators, as well as the availability of one noise reference per microphone pair. For spatially and temporally non-stationary noise fields, the proposed method leads to improved performance compared to widely used state-of-the-art reference methods in terms of both segmental SNR and beamformer response error.
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
The following notice applies to all IEEE publications:
© IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.