- Tytuł:
- Amended Adaptive Algorithm for Corpus Based Improved Speech Enhancement
- Autorzy:
-
Priya, P. Shanmuga
Nidhyananthan, S. Selva
Kumari, R. Shantha Selva - Powiązania:
- https://bibliotekanauki.pl/articles/226976.pdf
- Data publikacji:
- 2019
- Wydawca:
- Polska Akademia Nauk. Czytelnia Czasopism PAN
- Tematy:
-
least mean square
normalised least mean square
amended normalised least mean square
blind source separation - Opis:
- 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.
- Źródło:
-
International Journal of Electronics and Telecommunications; 2019, 65, 3; 513-517
2300-1933 - Pojawia się w:
- International Journal of Electronics and Telecommunications
- Dostawca treści:
- Biblioteka Nauki
Artykuł