Analysis of audio signal using various transforms for enhanced audio processing

Abstract

Audio Signals are the portrayal of sounds. It changes with respect to frequencies rather than time, and it shows more information in the frequency domain. So it is much appropriate to evaluate in the frequency domain rather than the time domain. By using different transforms like DFT, DST, DCT, MDCT, Integer MDCT, the time domain audio signal can be converted into a frequency domain signal. The signal is reconstructed to analyze the features like mean square error, Signal to noise ratio, Peak signal to noise ratio between the original and reconstructed signal. Other features like energy, entropy, zero crossing rates (ZCR) were also considered for the evaluation. In this paper, different audio file formats were taken for interpretation. It includes wave file, mp3 file, m4a file, aac file, where wave file is in uncompressed format and mp3, m4a, aac are in compressed format. These compressed files come under lossy compression. The above-mentioned features are used for applications like music information retrieval (MIR). MIR includes onset detection, pitch detection and to measure the noise and loudness of the music.