Study On Speech Compression Algorithm Based On Wavelet And Neural Networks

This article analyses speech signal acoustics characteristic, perception characteristic. Considering good character of the wavelet and neural networks in speech treatment, the method of integrating wavelet and BP neural networks is submitted to compress speech data. Speech compression system is divided into two parts: wavelet module and neural networks module. In the wavelet module part, speech signal is changed into wavelet coefficient at the first time. Then unimportant information of wavelet coefficient is compressed through wavelet threshold value. At last the important information of wavelet coefficient is quantized and encoded. In neural networks module part, the output is the binary data from wavelet module. At the same time fixed matrix is generated to be the input of neural networks. When the network is trained to be completed, the threshold value of the network is preserved. At last the threshold value is transferred and compression data purpose is reached. The simulated experiment is indicated that speech signal can be recognized when the compression ratio is around 31.