• Phase space parameters for neu...

Treffer: Phase space parameters for neural network based vowel recognition

Title:
Phase space parameters for neural network based vowel recognition
Authors:
PRAJITH, P, SREEKANTH, N. S, NARAYANAN, N. K
Source:
Neural information processing (Calcutta, 22-25 November 2004)Lecture notes in computer science. :1204-1209
Publisher Information:
Berlin: Springer, 2004.
Publication Year:
2004
Physical Description:
print, 9 ref
Original Material:
INIST-CNRS
Subject Terms:
Computer science, Informatique, Sciences exactes et technologie, Exact sciences and technology, Sciences appliquees, Applied sciences, Informatique; automatique theorique; systemes, Computer science; control theory; systems, Intelligence artificielle, Artificial intelligence, Reconnaissance et synthèse de la parole et du son. Linguistique, Speech and sound recognition and synthesis. Linguistics, Connexionnisme. Réseaux neuronaux, Connectionism. Neural networks, Algorithme rétropropagation, Backpropagation algorithm, Algoritmo retropropagación, Espace phase, Phase space, Espacio fase, Propagation erreur, Growth of error, Propagación error, Reconnaissance parole, Speech recognition, Reconocimiento voz, Réseau neuronal, Neural network, Red neuronal, Traitement signal, Signal processing, Procesamiento señal, Voyelle, Vowel, Vocal
Document Type:
Konferenz Conference Paper
File Description:
text
Language:
English
Author Affiliations:
School of Information Science & Technology, Kannur University, Thalassery campus, Palayad 670 661, India
ISSN:
0302-9743
Access URL:
http://pascal-francis.inist.fr/vibad/index.php?action=search&terms=16442562
Rights:
Copyright 2005 INIST-CNRS
CC BY 4.0
Sauf mention contraire ci-dessus, le contenu de cette notice bibliographique peut être utilisé dans le cadre d’une licence CC BY 4.0 Inist-CNRS / Unless otherwise stated above, the content of this bibliographic record may be used under a CC BY 4.0 licence by Inist-CNRS / A menos que se haya señalado antes, el contenido de este registro bibliográfico puede ser utilizado al amparo de una licencia CC BY 4.0 Inist-CNRS
Notes:
Computer science; theoretical automation; systems
Accession Number:
edscal.16442562
Database:
PASCAL Archive

Weitere Informationen

This paper presents the implementation of a neural network with error back propagation algorithm for the speech recognition application with Phase Space Point Distribution as the input parameter. By utilizing nonlinear or chaotic signal processing techniques to extract time domain based phase space features, a method is suggested for speech recognition. Two sets of experiments are presented in this paper. In the first, exploiting the theoretical results derived in nonlinear dynamics, a processing space called phase space is generated and a recognition parameter called Phase Space Point Distribution (PSPD) is extracted. In the second experiment Phase Space Map at a phase angle π/2 is reconstructed and PSPD is calculated. The output of a neural network with error back propagation algorithm demonstrate that phase space features contain substantial discriminatory power.