Speech Enhancement Based on Data-Driven Residual Gain Estimation

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초록

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.

키워드

speech enhancementnoise reductiondata-driven approachresidual gain estimation
제목
Speech Enhancement Based on Data-Driven Residual Gain Estimation
저자
Jin, Yu GwangKim, Nam SooChang, Joon-Hyuk
DOI
10.1587/transinf.E94.D.2537
발행일
2011-12
유형
Article
저널명
IEICE Transactions on Information and Systems
E94D
12
페이지
2537 ~ 2540