8th International Conference on Spoken Language Processing

Jeju Island, Korea
October 4-8, 2004

Improved Iterative Wiener Filtering for Non-Stationary Noise Speech Enhancement

T. V. Sreenivas, K. Sharath Rao, A. Sreenivasa Murthy

Indian Institute of Science, India

A clean speech VQ codebook has been shown to be effective in imposing intraframe constraints in Iterative Wiener Filtering (CCIWF) for speech enhancement. However, for time-varying noises, the performance is sub-optimum. We propose a smoothed noise update technique that uses the estimated signal spectrum for subsequent signal estimation. This leads to a more effective solution than the soft-decision based noise estimate found in literature. Further, the CCIWF performance is improved using codebook constraints in the LAR domain instead of LPC domain. Also, a new iteration initialization method is proposed which results in better enhancement in over 70% of the frames. Thus, we show that a combination of a robust parameter space, an effective initialization and continuous spectrum update significantly improves the performance of speech enhancement. Speech recognition results show that the new combination provides 10-20% increase in word recognition scores whereas simple spectral subtraction results in an actual decrease in recognition score.

Full Paper

Bibliographic reference.  Sreenivas, T. V. / Sharath Rao, K. / Sreenivasa Murthy, A. (2004): "Improved iterative wiener filtering for non-stationary noise speech enhancement", In INTERSPEECH-2004, 2713-2716.