Abstract
This paper presents a simulation and hardware implementation of a new audio compression scheme based on the fast Hartley transform in combination with a new modified run length encoding. The proposed algorithm consists of analyzing signals with fast Hartley Transform and then thresholding the ob-tained coefficients below a given threshold which are then encoded using a new approach of run length encoding. The thresholded coefficients are, finally, quantized and coded into binary stream. The experimental results show the ability of the fast Hartley transform to compress audio signals. Indeed, it concentrates the signal energy in a few coefficients and demonstrates the ability of the new approach of run length encoding to increase the compression factor. The results of the current work are compared with wavelet based compression by using objective assessments namely CR, SNR, PSNR and NRMSE. This study shows that the fast Hartley transform is more appropriate than wavelets one since it offers a higher compression ratio and a better speech quality. In addition, we have tested the audio compression system on DSP processor TMS320C6416.This test shows that our system fits with the real-time requirements and ensures a low complexity. The perceptual quality is evaluated with the Mean Opinion Score (MOS).
Highlights
The advancement of communication technology and the growth of the Internet have made speech compression a prime concern in the field of digital signal processing
In recent years many researches in the field of digital signal processing show interests on Discrete Hartley Transform (DHT) [14] [15][16].Computing the DHT directly from its definition is too slow which does not fit with real-time application in which the computational time has a great importance.In above context, we have proposed a real-time speech compression system based on Fast Hartley Transform www.ijacsa.thesai.org (IJACSA) International Journal of Advanced Computer Science and Applications, Vol 8, No 4, 2017 (FHT)
Several methods for subjective assessment are used in literature which are described in ITU-T Recommendation P.830.The most commonly used evaluation method is the absolute category rating (ACR) in which a group of listeners listen to audio sequences and judge the perceived quality according to a rating scale
Summary
The advancement of communication technology and the growth of the Internet have made speech compression a prime concern in the field of digital signal processing. Lossless compression methods represent the signal with a few bits while providing the same shape as the original speech signal at the decoder end, the run length encoding and the Huffman coding are the most known in this type. There are three key speech compression techniques, namely the waveform coding, parameter extraction and transformation methods. The waveform coding consists of removing correlation between speech samples to reduce the bit rate. It aims to minimize the error between the reconstructed and the original speech signal. The basic principle of Discrete Wavelet Transform (DWT) consists in separating the signal into two sets, one representing the general shape of the signal and the other representing its details.
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