Codebook Constrained Iterative Noise Cancellation with Applications to Speech Enhancement

The performance of widely-used adaptive noise canceling(ANC) deteriorates much when the desired signal is leaked into the reference channel or when there are uncorrelated noises present in the reference channel. This paper proposes a dual-microphone scheme, named Iterative Noise Canceling (INC), to overcome the drawbacks mentioned above. The proposed INC system, in which a codebook-based speech quality measure is employed to control a modified iterative Wiener filter (MIWF), can automatically reduce noises in the primary input until convergence occurs. In comparison with traditional ANC algorithm, the evaluation using real noises and voices recorded in a car shows the noise reduction performance is dramatically improved, even in cases that the reference SNR is close to 0 dB