Speech Enhancement Based on Data-Driven Residual Gain Estimation

Yu Gwang JIN  Nam Soo KIM  Joon-Hyuk CHANG  

IEICE TRANSACTIONS on Information and Systems   Vol.E94-D   No.12   pp.2537-2540
Publication Date: 2011/12/01
Online ISSN: 1745-1361
DOI: 10.1587/transinf.E94.D.2537
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Speech and Hearing
speech enhancement,  noise reduction,  data-driven approach,  residual gain estimation,  

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In this letter, we propose a novel speech enhancement algorithm based on data-driven residual gain estimation. The entire system consists of two stages. At the first stage, a conventional speech enhancement algorithm enhances the input signal while estimating several signal-to-noise ratio (SNR)-related parameters. The residual gain, which is estimated by a data-driven method, is applied to further enhance the signal at the second stage. A number of experimental results show that the proposed speech enhancement algorithm outperforms the conventional speech enhancement technique based on soft decision and the data-driven approach using SNR grid look-up table.