Speech Compression for Better Audibility using Wavelet Transformation with Adaptive Kalman Filtering

This paper deals with speech compression based on Discrete wavelet transforms and Adapive Kalman filter. English words were used for this experiment. This kalman filter with wavelet coding could successfully compress and reconstructed words with perfect audibility by using both waveform coding. But in general the Wavelet coding gives more accuracy for audibility. Here the proposed Adaptive Kalman filter with Wavelet Coding which gives more audibility than only Wavelet coding. In mobile communication systems, service providers are continuously met with the challenge of accommodating more users within a limited allocated bandwidth. For this reason, manufactures and service providers are continuously in search of low bit-rate speech coders that deliver toll-quality speech. The result obtained from Wavelet Coding was compared with Adaptive Kalman with Wavelet Coding. From the results we saw that the performance of Wavelet Coding with Adaptive Kalman Filter was better than wavelet transform. Keywords— Wavelet Transform coding (DWT), Adaptive Kalman filtering, Signal to Noise Ratio (SNR), Peak Signal to Noise Ratio (PSNR), Normalized Root Mean Square Error (NRMSE), Percentage of zero coefficients (PZEROS) , Compression Score (CS).