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Speech Enhancement using Segmental Non-Negative Matrix Factorization (SNMF) and Hidden Marvok Model (HMM)
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 119 - Number 6 |
| Year of Publication: 2015 |
| Authors: Barinder Singh, Karan Mahajan |
10.5120/21068-3738
|
Barinder Singh, Karan Mahajan . Speech Enhancement using Segmental Non-Negative Matrix Factorization (SNMF) and Hidden Marvok Model (HMM). International Journal of Computer Applications. 119, 6 ( June 2015), 1-2. DOI=10.5120/21068-3738
Abstract
Speech Enhancement refered as to improve quality or intelligibility of speech signal. Speech signal is often degraded by additive background noise like babble noise, train noise, restaurant noise etc. Speech enhancement aims at improving the performance of speech communication systems in noisy environments. This paper proposes a segmental NMF (SNMF) speech enhancement scheme to improve the conventional frame-wise NMF-based method. In this two algorithms are derived to decompose the original nonnegative matrix associated with the magnitude spectrogram, the first algorithm is used in the spectral domain and the second algorithm is used in the temporal domain . In this paper Hidden macro model and SNMF(S) for subjective learning (SNMF-S). Then the SNMF for the objective learning (SNMF-O) will be implemented.
References
- Hao-Teng Fan1, Jeih-weih Hung 1, Xugang Lu2, Syu-Siang Wang3 , and Yu Tsao3," Speech enhancement using segmental non negative matrix factorization, 2014 IEEE International Conference on Acoustic, Speech and Signal Processing (ICASSP).
- R. Martin, "Noise power spectral density estimation based on optimal smoothing and minimum statistics," IEEE Transactions on Speech and Audio Processing, 9(5), pp. 504–512, 2001.
- I. Cohen, "Noise spectrum estimation in adverse environments: Improved minima controlled recursive averaging," IEEE Transactions on Speech and Audio Processing, 11(5) ,pp. 466–475, 2003.
- S. Srinivasan, J. Samuelsson, and W. Kleijn, "Codebook driven short-term predictor parameter estimation for speech enhancement," IEEE Transactions on Audio, Speech, and Language Processing, 14(1), pp. 163–176, 2006.
- D. Y. Zhao and W. B. Kleijn, "HMM-based gain modelling for enhancement of speech in noise," IEEE Transactions on Audio, Speech, and Language Processing, 15(3), pp. 882–892, 2007.
- K. El-Maleh, A. Samouelian, and P. Kabal, "Frame level noise classification in mobile environments," in Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 237–240, 1999.
- Berdugo , B. and Cohen, "Noise estimation by minima controlled recursive averaging for robust speech enhancement" , IEEE Signal Proc. Letters, vol. 9, no. 1, pp. 12-15, Jan. 2002.
- C. Breithaupt and R. Martin,"MMSE estimation of magnitude-squared DFT coefficients with super-gaussian priors",? in Proc. IEEE Int. Conf. Acoust. , Speech, Signal Processing, pp. 848-851, 2003.
- Malah, D. , Cox, R. V. and Accardi, A. J. , "Tracking speech-presence uncertainty to improve speech enhancement in non-stationary noise environments,"? Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, vol. 2, pp. 789-792, 15-19 Mar 1999.
- Y. Ephraim," Speech Enhancement Using a Minimum Mean-Square Error Log-Spectral Amplitude Estimator", IEEE Transactions On Acoustics, Speech and Signal Processing 0096-35 18/8S/0400-0443, 1985.
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