SciELO - Scientific Electronic Library Online

 
vol.21 issue4Automatic Analysis of Annual Financial Reports: A Case StudyBeyond Pairwise Similarity: Quantifying and Characterizing Linguistic Similarity between Groups of Languages by MDL author indexsubject indexsearch form
Home Pagealphabetic serial listing  

Services on Demand

Journal

Article

Indicators

Related links

  • Have no similar articlesSimilars in SciELO

Share


Computación y Sistemas

Print version ISSN 1405-5546

Abstract

LAI, Wen-Hsing; YANG, Cheng-Jia  and  WANG, Siou-Lin. Post-Processing for the Mask of Computational Auditory Scene Analysis in Monaural Speech Segregation. Comp. y Sist. [online]. 2017, vol.21, n.4, pp.819-827. ISSN 1405-5546.  http://dx.doi.org/10.13053/cys-21-4-2846.

Speech segregation is one of the most difficult tasks in speech processing. This paper uses computational auditory scene analysis, support vector machine classifier, and post-processing on binary mask to separate speech from background noise. Mel-frequency cepstral coefficients and pitch are the two features used for support vector machine classification. Connected Component Labeling, Hole Filling, and Morphology are applied on the resulting binary mask as post-processing. Experimental results show that our method separates speech from background noise effectively.

Keywords : CASA; Connected Component Labeling; SVM.

        · text in English     · English ( pdf )