Audio Compression Using DCT and DWT Techniques

Abstract

In today’s world multimedia files are used, storage space required for these files is more and sound files have no option so ultimate solution for this is compression. Compression is nothing but high input stream of data converted into smaller size. Speech Compression is a field of digital signal processing that focuses on reducing bit-rate of speech signals to enhance transmission speed and storage requirement of fast developing multimedia. In many applications, such as the design of multimedia workstations and high quality audio transmission and storage, the goal is to achieve transparent coding of audio and speech signals at the lowest possible data rates. Therefore, the transmission and storage of information becomes costly. However, if we can use less data, both transmission and storage become cheaper. Further reduction in bit rate is an attractive proposition in applications like remote broadcast lines, studio links, satellite transmission of high quality audio and voice over internet. This paper explores a transform based methodology for compression of the speech signal. In this methodology, different transforms such as Discrete Wavelet Transform (DWT), Fast Fourier Transform (FFT) and Discrete Cosine Transform (DCT) are exploited. A comparative study of performance of different transforms is made in terms of Signal-to-noise ratio (SNR) and  Peak signal-to-noise ratio (PSNR). The mean compression ratio is also calculated for all the methods and compared. The simulation results included illustrate the effectiveness of these transforms in the field of data compression.

Keywords-DCT (Discrete cosine transform), DWT (Discrete wavelet transform), Quantization Compression Factor (CF), Signal to Noise ratio (SNR).