Wavelet Quantization of Noisy Speech Using Constrainedwiener

In this paper we propose an architecture for low bit rate coding of noisy speech. The input noisy speech is decomposed into multi-resolution signal components using wavelet transform. An iterative Wiener lter-ing is used at each level of wavelet analysis to enhance speech. The system model that evolves during enhancement is processed further to get optimal parameters for the quantization. A multistage vector quantizer is used for compression of decomposed speech. The enhanced speech is reconstructed at the receiving end by a VQ decoder and the necessary wavelet reconstruction network. The speech coding rate for the proposed architecture is estimated to be 2.8Kbps.