Speaker identification in noisy conditions using linear prediction of one-sided autocorrelation sequence

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To access the full text documents, please follow this link: http://hdl.handle.net/2117/88723

dc.contributor	Universitat Politècnica de Catalunya. Departament de Teoria del Senyal i Comunicacions
dc.contributor	Universitat Politècnica de Catalunya. VEU - Grup de Tractament de la Parla
dc.contributor.author	Hernando Pericás, Francisco Javier
dc.contributor.author	Nadeu Camprubí, Climent
dc.contributor.author	Villagrasa, C
dc.contributor.author	Monte Moreno, Enrique
dc.date	2004
dc.identifier.citation	Hernando, J., Nadeu, C., Villagrasa, C., Monte, E. Speaker identification in noisy conditions using linear prediction of one-sided autocorrelation sequence. A: International Conference on Spoken Language Processing. "ICSLP 94: 1994 International Conference on Spoken Language Processing: September 18-22, 1994: Pacific Convention Plaza Yokohama (PACIFICO), Yokohama, Japan". Yokohama: 2004, p. 1847-1850.
dc.identifier.uri	http://hdl.handle.net/2117/88723
dc.language.iso	eng
dc.rights	info:eu-repo/semantics/openAccess
dc.rights	http://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subject	Àrees temàtiques de la UPC::Enginyeria de la telecomunicació
dc.subject	Àrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la parla i del senyal acústic
dc.subject	Speech processing systems
dc.subject	Signal processing
dc.subject	Processament de la parla
dc.subject	Tractament del senyal
dc.title	Speaker identification in noisy conditions using linear prediction of one-sided autocorrelation sequence
dc.type	info:eu-repo/semantics/publishedVersion
dc.type	info:eu-repo/semantics/conferenceObject
dc.description.abstract	The OSALPC (One-Sided Autocorrelation Linear Predictive Coding) representation of the speech signal has shown to be attractive for speech recognition because of its simplicity and its high recognition performance with respect to the standard LPC in severe noisy conditions. In this paper the OSALPC technique is applied to the problem of speaker identification in noisy conditions. As shown with experimental results, using additive white noise, that technique also achieves much better results than both LPC and mel-cepstrum parameterizations in this task.
dc.description.abstract	Peer Reviewed

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