A segmentation algorithm based on acoustical features using a self organizing neural network.

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Title:	A segmentation algorithm based on acoustical features using a self organizing neural network.
Author:	Monte Moreno, Enrique
Other authors:	Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions; Universitat Politècnica de Catalunya. VEU - Grup de Tractament de la Parla
Abstract:	In this paper we investigate the use of a self-organizing map in an acoustic segmentation task. The aim is to obtain a limited number of acoustic classes and to segment whenever a change in the class between two adjacent frames occurs. Energy in different frequency ranges is used as input in the map training process. A structure based on a Kohonen map connected to a neural network trained with the back-propagation algorithm is proposed.
Abstract:	Peer Reviewed
Subject(s):	-Àrees temàtiques de la UPC::Enginyeria de la telecomunicació -Telecommunication -Kohonen map -Neural networks -Segmentation. -Telecomunicació
Rights:	http://creativecommons.org/licenses/by-nc-nd/3.0/es/
Document type:	Article - Published version Conference Object
Published by:	. EUROSPEECH
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