Some fast higher order ar estimation techniques applied to parametric wiener filtering

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To access the full text documents, please follow this link: http://hdl.handle.net/2117/88456

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	Salavedra Molí, Josep
dc.contributor.author	Masgrau Gómez, Enrique José
dc.contributor.author	Moreno Bilbao, M. Asunción
dc.contributor.author	Estarellas, J
dc.contributor.author	Hernando Pericás, Francisco Javier
dc.date	2004
dc.identifier.citation	Salavedra, J., Masgrau, E., Moreno, A., Estarellas, J., Hernando, J. Some fast higher order ar estimation techniques applied to parametric wiener filtering. 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. 1655-1658.
dc.identifier.uri	http://hdl.handle.net/2117/88456
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	Algorithms
dc.subject	Processament de la parla
dc.subject	Algorismes
dc.title	Some fast higher order ar estimation techniques applied to parametric wiener filtering
dc.type	info:eu-repo/semantics/publishedVersion
dc.type	info:eu-repo/semantics/conferenceObject
dc.description.abstract	Some Speech Enhancement algorithms based on the iterative Wiener filtering Method due to L1m-Oppenheim [2] are presented. In the original Lim-Oppenheim algorithm, speech AR estimation is carried out using classic second-order analysis, but our algorithms consider a more robust AR modelling. Two different strategies of speech AR estimation are presented and both estimators are trying to see as less amount of noise as possible. First one uses a previous One-Sided Autocorrelation computation, that is a pole-preserving function, and the actual SNR m the second-order LPC analysis is increased. Second one combines advantages of Higher-Order Statistics [1] with a linear combination of AR coefficients, belonging to two consecutive overlapped frames, to assess a less disturbed speech estimation.
dc.description.abstract	Peer Reviewed

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