Amended Adaptive Algorithm for Corpus Based Improved Speech Enhancement
Speech enhancement objective is to improve the noisy speech signals for human perception. The intention of speech enhancement algorithm is to improve the performance of the communication, when the signal is occluded by noise. The quality and intelligibility of speech is reduced because of the presen...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Polish Academy of Sciences
2019-09-01
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| Series: | International Journal of Electronics and Telecommunications |
| Subjects: | |
| Online Access: | https://journals.pan.pl/Content/113311/PDF/69.pdf |
| _version_ | 1811314190018674688 |
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| author | P. Shanmuga Priya S. Selva Nidhyananthan R. Shantha Selva Kumari |
| author_facet | P. Shanmuga Priya S. Selva Nidhyananthan R. Shantha Selva Kumari |
| author_sort | P. Shanmuga Priya |
| collection | DOAJ |
| description | Speech enhancement objective is to improve the noisy speech signals for human perception. The intention of speech enhancement algorithm is to improve the performance of the communication, when the signal is occluded by noise. The quality and intelligibility of speech is reduced because of the presence of background noise. There are various adaptive filtering algorithms for speech enhancement. The existing least mean square and normalised least mean square algorithms have the problem of choosing the step size that guarantees the stability of the algorithm. To overcome this problem, we focus on speech enhancement by amended adaptive filtering. The proposed algorithm follows blind source separation strategy using adaptive filtering. Comparison of existing adaptive filtering algorithms with proposed algorithm justifies the amendment incorporated in this paper. Taking the objective criteria into account the algorithms has been tested for segmental signal to noise ratio (SegSNR), segmental mean square error (SegMSE), signal to noise ratio and mean square error. The proposed algorithm can be used for hand-free cell phone, hearing aids and teleconferencing systems. |
| first_indexed | 2024-04-13T11:08:49Z |
| format | Article |
| id | doaj.art-53501513cbd04bc7902b318b18c3b6d9 |
| institution | Directory Open Access Journal |
| issn | 2081-8491 2300-1933 |
| language | English |
| last_indexed | 2024-04-13T11:08:49Z |
| publishDate | 2019-09-01 |
| publisher | Polish Academy of Sciences |
| record_format | Article |
| series | International Journal of Electronics and Telecommunications |
| spelling | doaj.art-53501513cbd04bc7902b318b18c3b6d92022-12-22T02:49:12ZengPolish Academy of SciencesInternational Journal of Electronics and Telecommunications2081-84912300-19332019-09-01vol. 65No 3513517https://doi.org/10.24425/ijet.2019.129807Amended Adaptive Algorithm for Corpus Based Improved Speech EnhancementP. Shanmuga PriyaS. Selva NidhyananthanR. Shantha Selva KumariSpeech enhancement objective is to improve the noisy speech signals for human perception. The intention of speech enhancement algorithm is to improve the performance of the communication, when the signal is occluded by noise. The quality and intelligibility of speech is reduced because of the presence of background noise. There are various adaptive filtering algorithms for speech enhancement. The existing least mean square and normalised least mean square algorithms have the problem of choosing the step size that guarantees the stability of the algorithm. To overcome this problem, we focus on speech enhancement by amended adaptive filtering. The proposed algorithm follows blind source separation strategy using adaptive filtering. Comparison of existing adaptive filtering algorithms with proposed algorithm justifies the amendment incorporated in this paper. Taking the objective criteria into account the algorithms has been tested for segmental signal to noise ratio (SegSNR), segmental mean square error (SegMSE), signal to noise ratio and mean square error. The proposed algorithm can be used for hand-free cell phone, hearing aids and teleconferencing systems.https://journals.pan.pl/Content/113311/PDF/69.pdfleast mean squaresnormalised least mean squareamended normalised least mean squareblind source separation |
| spellingShingle | P. Shanmuga Priya S. Selva Nidhyananthan R. Shantha Selva Kumari Amended Adaptive Algorithm for Corpus Based Improved Speech Enhancement International Journal of Electronics and Telecommunications least mean squares normalised least mean square amended normalised least mean square blind source separation |
| title | Amended Adaptive Algorithm for Corpus Based Improved Speech Enhancement |
| title_full | Amended Adaptive Algorithm for Corpus Based Improved Speech Enhancement |
| title_fullStr | Amended Adaptive Algorithm for Corpus Based Improved Speech Enhancement |
| title_full_unstemmed | Amended Adaptive Algorithm for Corpus Based Improved Speech Enhancement |
| title_short | Amended Adaptive Algorithm for Corpus Based Improved Speech Enhancement |
| title_sort | amended adaptive algorithm for corpus based improved speech enhancement |
| topic | least mean squares normalised least mean square amended normalised least mean square blind source separation |
| url | https://journals.pan.pl/Content/113311/PDF/69.pdf |
| work_keys_str_mv | AT pshanmugapriya amendedadaptivealgorithmforcorpusbasedimprovedspeechenhancement AT sselvanidhyananthan amendedadaptivealgorithmforcorpusbasedimprovedspeechenhancement AT rshanthaselvakumari amendedadaptivealgorithmforcorpusbasedimprovedspeechenhancement |