Analysis of PEAQ Model using Wavelet Decomposition Techniques

Digital broadcasting, internet audio and music database make use of audio compression and coding techniques to reduce high quality audio signal without impairing its perceptual quality. Audio signal compression is the lossy compression technique, It converts original converting audio signal into compressed bitstream. The compressed audio bitstream is decoded at the decoder to produce a close approximation of the original signal. For the purpose of improving the coding this work attempts to verify the perceptual evaluation of audio quality (PEAQ) model in BS.1387 using wavelet decomposition techniques. Finally the comparison of masking threshold for sub-bands using Wavelet techniques and Fast Fourier transform (FFT) will be done. Data compression refers to way of reducing data size without affecting the quality of the data; Audio compression is form of data compression. To acquire compressed audio, different audio compression methods have been contrived and implemented. These methods vary from simple technique to most advance and complex that takes sensitivity of the human ear. In the process of audio compression perceptual limitation of human ear is exploited. This Limitation in human hearing system is used to remove perceptually irrelevant audio signal. MPEG Audio compression technique algorithm achieves compression by exploiting the perceptual limitation of the human ear. By applying audio compression algorithms it is possible to get compact digital representations of audio signals for efficient transmission without impairing the quality at the receiving end. The main purpose of the audio compression is to represent the audio signal with a less number of bits while achieving transparent signal reproduction. The absolute threshold of hearing (ATH) is used to characterize the amount of energy needed in a pure tone such that it can be detected by a listener in a noiseless environment. The absolute threshold is typically expressed in terms of dB SPL. The frequency dependence of this threshold was quantified as early as 1940, when Fletcher reported test results for a range of listeners that were generated in a National Institutes of Health study of typical American hearing acuity. The quiet (absolute) threshold is well approximated by the nonlinear function (1)(6). Absolute threshold of hearing is used to shape the coding distortion spectrum is the first step toward perceptual coding. Absolute threshold is of limited value in the coding context. Finding threshold for spectrally complex quantization noise is a modified version of the absolute threshold, with its shape