Evaluations on underdetermined blind source separation in adverse environments using time-frequency masking
The successful implementation of speech processing systems in the real world depends on its ability to handle adverse acoustic conditions with undesirable factors such as room reverberation and background noise. In this study, an extension to the established multiple sensors degenerate unmixing esti...
| Main Authors: | , , , |
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| Format: | Journal Article |
| Published: |
2013
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| Online Access: | http://hdl.handle.net/20.500.11937/7701 |
| _version_ | 1848745445630672896 |
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| author | Jafari, I. Haque, S. Togneri, R. Nordholm, Sven |
| author_facet | Jafari, I. Haque, S. Togneri, R. Nordholm, Sven |
| author_sort | Jafari, I. |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | The successful implementation of speech processing systems in the real world depends on its ability to handle adverse acoustic conditions with undesirable factors such as room reverberation and background noise. In this study, an extension to the established multiple sensors degenerate unmixing estimation technique (MENUET) algorithm for blind source separation is proposed based on the fuzzy c-means clustering to yield improvements in separation ability for underdetermined situations using a nonlinear microphone array. However, rather than test the blind source separation ability solely on reverberant conditions, this paper extends this to include a variety of simulated and real-world noisy environments. Results reported encouraging separation ability and improved perceptual quality of the separated sources for such adverse conditions. Not only does this establish this proposed methodology as a credible improvement to the system, but also implies further applicability in areas such as noise suppression in adverse acoustic environments. |
| first_indexed | 2025-11-14T06:17:29Z |
| format | Journal Article |
| id | curtin-20.500.11937-7701 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T06:17:29Z |
| publishDate | 2013 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-77012017-09-13T14:33:46Z Evaluations on underdetermined blind source separation in adverse environments using time-frequency masking Jafari, I. Haque, S. Togneri, R. Nordholm, Sven The successful implementation of speech processing systems in the real world depends on its ability to handle adverse acoustic conditions with undesirable factors such as room reverberation and background noise. In this study, an extension to the established multiple sensors degenerate unmixing estimation technique (MENUET) algorithm for blind source separation is proposed based on the fuzzy c-means clustering to yield improvements in separation ability for underdetermined situations using a nonlinear microphone array. However, rather than test the blind source separation ability solely on reverberant conditions, this paper extends this to include a variety of simulated and real-world noisy environments. Results reported encouraging separation ability and improved perceptual quality of the separated sources for such adverse conditions. Not only does this establish this proposed methodology as a credible improvement to the system, but also implies further applicability in areas such as noise suppression in adverse acoustic environments. 2013 Journal Article http://hdl.handle.net/20.500.11937/7701 10.1186/1687-6180-2013-162 fulltext |
| spellingShingle | Jafari, I. Haque, S. Togneri, R. Nordholm, Sven Evaluations on underdetermined blind source separation in adverse environments using time-frequency masking |
| title | Evaluations on underdetermined blind source separation in adverse environments using time-frequency masking |
| title_full | Evaluations on underdetermined blind source separation in adverse environments using time-frequency masking |
| title_fullStr | Evaluations on underdetermined blind source separation in adverse environments using time-frequency masking |
| title_full_unstemmed | Evaluations on underdetermined blind source separation in adverse environments using time-frequency masking |
| title_short | Evaluations on underdetermined blind source separation in adverse environments using time-frequency masking |
| title_sort | evaluations on underdetermined blind source separation in adverse environments using time-frequency masking |
| url | http://hdl.handle.net/20.500.11937/7701 |