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Speech Segregation based on Pitch Track Correction and Music-Speech ClassificationKIM, H.-G. , JANG, G.-J. , PARK, J.-S. , KIM, J.-H. , OH, Y.-H.
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source separation, speech processing, speech analysis, signal denoising, noise cancellation
processing(7), neural(6), signal(5), separation(5), music(5), auditory(5), speech(4), negative(4), factorization(4)
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About this article
Date of Publication: 2012-05-30
Volume 12, Issue 2, Year 2012, On page(s): 15 - 20
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2012.02003
Web of Science Accession Number: 000305608000003
SCOPUS ID: 84865301789
A novel approach for pitch track correction and music-speech classification is proposed in order to improve the performance of the speech segregation system. The proposed pitch track correction method adjusts unreliable pitch estimates from adjacent reliable pitch streaks, in contrast to the previous approach using a single pitch streak which is the longest among the reliable pitch streaks in a sentence. The proposed music and speech classification method finds continuous pitch streaks of the mixture, and labels each streak as music-dominant or speech-dominant based on the observation that music pitch seldom changes in a short-time period whereas speech pitch fluctuates a lot. The speech segregation results for mixtures of speech and various competing sound sources demonstrated that the proposed methods are superior to the conventional method, especially for mixtures of speech and music signals.
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 Particle filtering based pitch sequence correction for monaural speech segregation, Kim, Han-Gyu, Jang, Gil-Jin, Park, Jeong-Sik, Kim, Ji-Hwan, Oh, Yung-Hwan, International Journal of Imaging Systems and Technology, ISSN 0899-9457, Issue 1, Volume 23, 2013.
Digital Object Identifier: 10.1002/ima.22039 [CrossRef]
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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania
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