New hos-based parameter estimation methods for speech recognition in noisy environments

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To access the full text documents, please follow this link: http://hdl.handle.net/2117/101323

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	Universitat Politècnica de Catalunya. SPCOM - Grup de Recerca de Processament del Senyal i Comunicacions
dc.contributor.author	Moreno Bilbao, M. Asunción
dc.contributor.author	Tortola, S
dc.contributor.author	Vidal Manzano, José
dc.contributor.author	Rodríguez Fonollosa, José Adrián
dc.date	1995
dc.identifier.citation	Moreno, A., Tortola, S., Vidal, J., Fonollosa, José A. R. New hos-based parameter estimation methods for speech recognition in noisy environments. A: IEEE International Conference on Acoustics, Speech, and Signal Processing. "ICASSP 1995: IEEE International Conference on Acoustics, Speech and Signal Processing: May 9-12, 1995". Detroit, Michigan: . S.N., 1995, p. 429-432.
dc.identifier.citation	10.1109/ICASSP.1995.479613
dc.identifier.uri	http://hdl.handle.net/2117/101323
dc.language.iso	eng
dc.publisher	. S.N.
dc.relation	http://ieeexplore.ieee.org/document/479613/
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	Telecommunication
dc.subject	Noise
dc.subject	Speech processing
dc.subject	Speech recognition
dc.subject	Parameter estimation
dc.subject	Higher order statistics
dc.subject	Correlation methods
dc.subject	Telecomunicació
dc.title	New hos-based parameter estimation methods for speech recognition in noisy environments
dc.type	info:eu-repo/semantics/publishedVersion
dc.type	info:eu-repo/semantics/conferenceObject
dc.description.abstract	The problem of recognition in noisy environments is addressed. Often, a recognition system is used in a noisy environment and there is no possibility of training it with noisy samples. Classical speech analysis techniques are based on second-order statistics and their performance dramatically decreases when noise is present in the signal under analysis. New methods based on higher order statistics (HOS) are applied in a recognition system and compared against the autocorrelation method. Cumulant-based methods show better performance than autocorrelation-based methods for low SNR
dc.description.abstract	Peer Reviewed

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