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Convention Paper

A Non-linear Rhythm-Based Style Classifciation for Broadcast Speech-Music Discrimination

Authors: Batlle, Eloi; Guaus, Enric

AES Convention 116 · Paper 6013 · May 2004

Abstract

Speech-Music discriminators are usually designed under some rigid constrains. This paper deals with a more general Speech-Music Discriminator successfully used in AIDA project. The system is based on a Hidden Markov Model style classification process in which the styles are grouped into two major categories: Speech or Music. The goals of this sub-system are (1)the expandible possibilities with the addition of some new styles (like "phone female voice"), (2)the use of new rhytmical descriptors in combination with other typical ones and (3)the robustness of our speech/music discriminator in many different environments by using some Mathematical Morphology and non-linear post-processing techniques. The techniques used in our system allow a fast track in changes between styles and, thus, typical confusions in commercials can be easily cleaned. The accuracy of this system can be up to a 94.3% in broadcast radio environment.

Details

Published in
AES Convention 116
AES Convention
116
Paper number
6013
Publication date
May 6, 2004
Session subject
Audio Archiving, Storage, and Restoration: Content Management
Affiliation
Audiovisual Institute, Pompeu Fabra University, Barcelona, Spain (See document for exact affiliation information.)
Type
Convention Paper