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dc.contributor.author
Di Persia, Leandro Ezequiel  
dc.contributor.author
Milone, Diego Humberto  
dc.contributor.author
Yanagida, M.  
dc.date.available
2020-04-06T15:28:36Z  
dc.date.issued
2009-02  
dc.identifier.citation
Di Persia, Leandro Ezequiel; Milone, Diego Humberto; Yanagida, M.; Indeterminacy Free Frequency-Domain Blind Separation of Reverberant Audio Sources; Institute of Electrical and Electronics Engineers; Ieee Transactions On Audio Speech And Language Processing; 17; 2; 2-2009; 299-311  
dc.identifier.issn
1558-7916  
dc.identifier.uri
http://hdl.handle.net/11336/102035  
dc.description.abstract
Blind separation of convolutive mixtures is a very complicated task that has applications in many fields of speech and audio processing, such as hearing aids and man?machine interfaces. One of the proposed solutions is the frequency-domain independent component analysis. The main disadvantage of this method is the presence of permutation ambiguities among con- secutive frequency bins. Moreover, this problem is worst when reverberation time increases. Presented in this paper is a new frequency-domain method, that uses a simplified mixing model, where the impulse responses from one source to each microphone are expressed as scaled and delayed versions of one of these impulse responses. This assumption, based on the similitude among waveforms of the impulse responses, is valid for a small spacing of the microphones. Under this model, separation is per- formed without any permutation or amplitude ambiguity among consecutive frequency bins. This new method is aimed mainly to obtain separation, with a small reduction of reverberation. Nevertheless, as the reverberation is included in the model, the new method is capable of performing separation for a wide range of reverberant conditions, with very high speed. The separation quality is evaluated using a perceptually designed objective mea- sure. Also, an automatic speech recognition system is used to test the advantages of the algorithm in a real application. Very good results are obtained for both, artificial and real mixtures. The results are significantly better than those by other standard blind source separation algorithms.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Institute of Electrical and Electronics Engineers  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
Blind Source Separation  
dc.subject
Reverberation  
dc.subject
Independent Component Analysis  
dc.subject
Speech Enhancement  
dc.subject.classification
Control Automático y Robótica  
dc.subject.classification
Ingeniería Eléctrica, Ingeniería Electrónica e Ingeniería de la Información  
dc.subject.classification
INGENIERÍAS Y TECNOLOGÍAS  
dc.title
Indeterminacy Free Frequency-Domain Blind Separation of Reverberant Audio Sources  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2020-04-02T13:21:32Z  
dc.journal.volume
17  
dc.journal.number
2  
dc.journal.pagination
299-311  
dc.journal.pais
Estados Unidos  
dc.description.fil
Fil: Di Persia, Leandro Ezequiel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; Argentina  
dc.description.fil
Fil: Milone, Diego Humberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional. Universidad Nacional del Litoral. Facultad de Ingeniería y Ciencias Hídricas. Instituto de Investigación en Señales, Sistemas e Inteligencia Computacional; Argentina  
dc.description.fil
Fil: Yanagida, M.. Doshisha University; Japón  
dc.journal.title
Ieee Transactions On Audio Speech And Language Processing  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1109/TASL.2008.2009568