Discrimination between Speech and Music signal
Sumit Kumar Banchhor

Sumit Kumar Banchhor, Electronics and Telecommunication, Chhattisgarh Swami Vivekananda Technical University, GD Rungta College of Engineering and Technology, Bhilai, India
Manuscript received on July 01, 2012. | Revised Manuscript received on July 04, 2012. | Manuscript published on July 05, 2012. | PP: 28-31 | Volume-2, Issue-3, July 2012. | Retrieval Number: C0662052312/2012©BEIESP
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© The Authors. Published By: Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Over the last few years major efforts have been made to develop methods for extracting information from audio-visual media, in order that they may be stored and retrieved in databases automatically. In this work we deal with the characterization of an audio signal, which is a part of a larger audio-visual system. Our goal was first to develop a system for segmentation of the audio signal, and then classify into one of two main categories: speech or music. The basic characteristics are computed in 2sec intervals. The result shows that the estimation of short time energy reflects more effectively the difference in human voice and musical instrument than zero crossing rate and spectrum flux.

Keywords: Speech/music classification, audio segmentation, zero crossing rate, short time energy, and spectrum flux.