Integration of Speech/Music Discrimination and Mood Classification with Audio Feature Extraction

In the area of multimedia indexing and processing, a big challenge is to classify the mood of the listener through music. It is also a prodigious challenge to separate the noisy signals into speech, music or silence. Mood of the person may depend upon music. According to the music psychologists, behavior of a person is defined by his mood. Thus, this research evaluates the features of audio that have substantial impact on mood of a person and focuses that how to distinguish the speech signals and music from audio file at the same time. Many audio extraction algorithms have been hashed out in this paper and proposes one MMCAD (music mood classification & Audio discrimination) which is the integration of mood detector and speech / music discriminator with better efficiency and accuracy.