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Paper Details
Paper Title
Speech/music classification using PLP and AANN
Authors
R. Thiruvengatanadhan
Abstract
The term audio is used to indicate all kinds of audio signals, such as speech, music as well as more general sound signals and their combinations. This paper deals with the Speech/Music classification problem, starting from a set of features extracted directly from audio data. Automatic audio classification is very useful in audio indexing; content based audio retrieval and online audio distribution. The accuracy of the classification relies on the strength of the features and classification scheme. In this work Perceptual Linear Prediction (PLP) features are extracted from the input signal. After feature extraction, classification is carried out, using Auto associative neural network (AANN) model. The proposed feature extraction and classification models results in better accuracy in speech/music classification.
Keywords- Speech, Music, Feature Extraction, PLP, AANN.
Publication Details
Unique Identification Number - IJEDR1901018Page Number(s) - 87-90Pubished in - Volume 7 | Issue 1 | January 2019DOI (Digital Object Identifier) - Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
R. Thiruvengatanadhan, "Speech/music classification using PLP and AANN", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.7, Issue 1, pp.87-90, January 2019, Available at :http://www.ijedr.org/papers/IJEDR1901018.pdf
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