Vector Quantization of Speech with Noise Cancellation

This thesis is an investigation of robust vector quantization, with the purpose of providing a system for the application of data compression and speech enhancement. Vector quantization is widely used in data compression systems. However, the performance of these systems will degrade in a noisy environment. The proposed robust vector quantization system solves the problem of optimal quantization of a signal affected by additive noise in a conventional framework of vector quantization. A noise estimate is used to adapt the vector quantization codebook to the specific noisy environment, and a spectral mapping technique is used to obtain noisecancelled parameters. The system is supposed to be suitable for dealing with any type of additive noise sources. The experimental results show a significant improvement for a considerable range of signal-to-noise ratios. For my parents, with love