An effective framework for speech and music segregation
Joint Authors
Irtaza, Aun
Javed, Ali
Sajid, Sidra
Source
The International Arab Journal of Information Technology
Issue
Vol. 17, Issue 4 (31 Jul. 2020), pp.507-514, 8 p.
Publisher
Zarqa University Deanship of Scientific Research
Publication Date
2020-07-31
Country of Publication
Jordan
No. of Pages
8
Main Subjects
Information Technology and Computer Science
Abstract EN
Speech and music segregation from a single channel is a challenging task due to background interference and intermingled signals of voice and music channels.
It is of immense importance due to its utility in wide range of applications such as music information retrieval, singer identification, lyrics recognition and alignment.
This paper presents an effective method for speech and music segregation.
Considering the repeating nature of music, we first detect the local repeating structures in the signal using a locally defined window for each segment.
After detecting the repeating structure, we extract them and perform separation using a soft time-frequency mask.
We apply an ideal binary mask to enhance the speech and music intelligibility.
We evaluated the proposed method on the mixtures set at -5 dB, 0 dB, 5 dB from Multimedia Information Retrieval-1000 clips (MIR-1K) dataset.
Experimental results demonstrate that the proposed method for speech and music segregation outperforms the existing state-of-the-art methods in terms of Global-Normalized-Signal-to-Distortion Ratio (GNSDR) values.
American Psychological Association (APA)
Sajid, Sidra& Javed, Ali& Irtaza, Aun. 2020. An effective framework for speech and music segregation. The International Arab Journal of Information Technology،Vol. 17, no. 4, pp.507-514.
https://search.emarefa.net/detail/BIM-1430886
Modern Language Association (MLA)
Sajid, Sidra…[et al.]. An effective framework for speech and music segregation. The International Arab Journal of Information Technology Vol. 17, no. 4 (Jul. 2020), pp.507-514.
https://search.emarefa.net/detail/BIM-1430886
American Medical Association (AMA)
Sajid, Sidra& Javed, Ali& Irtaza, Aun. An effective framework for speech and music segregation. The International Arab Journal of Information Technology. 2020. Vol. 17, no. 4, pp.507-514.
https://search.emarefa.net/detail/BIM-1430886
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 513-514
Record ID
BIM-1430886