Journal of Information Technology & Software Engineering
Open Access

A wavelet-based speech/music classification using texture image information

Global Summit and Expo on Multimedia & Applications

August 10-11, 2015 Birmingham, UK

Kun-Ching Wang

Scientific Tracks Abstracts: J Inform Tech Soft Engg

Abstract :

This paper presents a wavelet-based speech/music classification using spectrogram image feature, (SIF). The SIF can
efficiently reflect the visual signature characteristics from the sound’s time-frequency representation. First, the input audio/
speech sound is decomposed by wavelet packet transform into different subband levels. Through useful subband selection, we
can keep the subbands, which contain rich texture information, are used as features for this discrimination problem. Finally,
the support vector machine (SVM) is then used to classy the speech segment or audio segment.

Biography :

Kun-Ching Wang is a faculty member of Department of Information Technology & Communication in Shih Chien University, Taiwan.