Speech Compression based on Psychoacoustic Model and A General Approach for Filter Bank Design using Optimization

In this paper we propose a new speech compression technique based on the application of a psychoacoustic model combined with a general approach for Filter Bank Design using optimization. This technique is a modified version of the compression technique using a MDCT (Modified Discrete Cosine Transform) filter banks of 32 filters each and a psychoacoustic model. The two techniques are evaluated and compared with each other by computing bits before and bits after compression. They are tested on different speech signals and the obtained simulation results show that the proposed technique outperforms the second technique and this in term of compressed file size. In term of speech quality, the outputs speech signals of the proposed compression system are with good quality. This is justified by SNR, PSNR, NRMSE and PESQ computation.