International Journal of Nonlinear Analysis and Applications
The impact of subband pause noise on the sensitivity of detection methods
Document Type : Research Paper
Authors
Al-Esraa University College, Baghdad, Iraq
Abstract
Through the use of subband analysis, the article presents a method for selecting pauses in speech communications. An additive blending of normally distributed noise was used in the sensitivity analysis. In various noise / signal respects, the probability of making a bad decision has been identified. The findings show that the proposed sub-band method is stable when subjected to additive noise effects.
Keywords
[1] V. B. Sadov, To a question of automatic control of the drive of the sucker rod pump, Bull. South Ural State University, Ser. Comput. Tech. Cont. Radio Elec. 13(eLikelihood, Routledge, 203) (2013) 46–53.
[2] A. Azzalini, Statistical Inference: Based on TheLikelihood, Routledge, 2017.
[3] L. Karray and Arnaud Martin, Towards improving speech detection robustness for speech recognition in adverse conditions, Speech Commun. 40(3) (2003) 261–276.
[4] J. Ramirez, J. C. Segura, C. Ben´ıtez, A. de la Torre and A. Rubio, A new adaptive long-term spectral estimation voice activity detector, Eighth Europ. Conf. Speech Commun. Tech. 2003.
[5] J. Ram´ırez, J. C. Segura, C. Benitez, A. de la Torre and A. Rubio, An effective subband OSF-based VAD with noise reduction for robust speech recognition, IEEE Transactions on Speech and Audio Proc. 13(6) (2005) 1119–1129.
[6] A. Benyassine, E. Shlomot, H.-Y. Su, D. Massaloux, C. Lamblin and J.-P. Petit, ITU-T Recommendation G. 729 Annex B: a silence compression scheme for use with G. 729 optimized for V. 70 digital simultaneous voice and data applications, IEEE Commun. Mag. 35(9) (1997) 64–73.
[7] Sangwan, Abhijeet, et al, VAD techniques for real-time speech transmission on the internet, 5th IEEE International Conference on High Speed Networks and Multimedia Communication (Cat. No. 02EX612). IEEE, 2002.
[8] F. Basbug, K. Swaminathan and S. Nandkumar, Noise reduction and echo cancellation front-end for speech codecs, IEEE Trans. Speech Audio Proc. 11(1) (2003) 1–13.
[9] S. Gustafsson, R. Martin and P. Vary, A psychoacoustic approach to combined acoustic echo cancellation and noise reduction, IEEE Trans. Speech Audio Proc. 10(5) (2002) 245–256.
[10] S. Bradley, J. Backman, S. von Hunerbein and T. Wu, The mechanisms creating wind noise in microphones, Audio Engin. Soc. Conven. 114. Audio Engin. Soc. 2003.
[11] S. Morgan, and R. Raspet, Investigation of the mechanisms of low-frequency wind noise generation outdoors, J. Acoust. Soc. Amer. 92(2) (1992) 1180–1183.
[12] J. Wang, P. Du, T. Niu and W. Yang, A novel hybrid system based on a new proposed algorithm—multi-objective whale optimization algorithm for wind speed forecasting, Appl. Energy, 208 (2017) 344–360.
[13] Q. Shakir kadhima, H. Kh. Obayes, M. H. Rashid, S. H. Abdul-zahrah and O. Khudhayer Obayes Features of molecules accumulation in the triplet state at excitation of the organic compounds by rectangular pulses, Organic Elect. 64 (2019) 202–204.
[3] L. Karray and Arnaud Martin, Towards improving speech detection robustness for speech recognition in adverse conditions, Speech Commun. 40(3) (2003) 261–276.
[4] J. Ramirez, J. C. Segura, C. Ben´ıtez, A. de la Torre and A. Rubio, A new adaptive long-term spectral estimation voice activity detector, Eighth Europ. Conf. Speech Commun. Tech. 2003.
[5] J. Ram´ırez, J. C. Segura, C. Benitez, A. de la Torre and A. Rubio, An effective subband OSF-based VAD with noise reduction for robust speech recognition, IEEE Transactions on Speech and Audio Proc. 13(6) (2005) 1119–1129.
[6] A. Benyassine, E. Shlomot, H.-Y. Su, D. Massaloux, C. Lamblin and J.-P. Petit, ITU-T Recommendation G. 729 Annex B: a silence compression scheme for use with G. 729 optimized for V. 70 digital simultaneous voice and data applications, IEEE Commun. Mag. 35(9) (1997) 64–73.
[7] Sangwan, Abhijeet, et al, VAD techniques for real-time speech transmission on the internet, 5th IEEE International Conference on High Speed Networks and Multimedia Communication (Cat. No. 02EX612). IEEE, 2002.
[8] F. Basbug, K. Swaminathan and S. Nandkumar, Noise reduction and echo cancellation front-end for speech codecs, IEEE Trans. Speech Audio Proc. 11(1) (2003) 1–13.
[9] S. Gustafsson, R. Martin and P. Vary, A psychoacoustic approach to combined acoustic echo cancellation and noise reduction, IEEE Trans. Speech Audio Proc. 10(5) (2002) 245–256.
[10] S. Bradley, J. Backman, S. von Hunerbein and T. Wu, The mechanisms creating wind noise in microphones, Audio Engin. Soc. Conven. 114. Audio Engin. Soc. 2003.
[11] S. Morgan, and R. Raspet, Investigation of the mechanisms of low-frequency wind noise generation outdoors, J. Acoust. Soc. Amer. 92(2) (1992) 1180–1183.
[12] J. Wang, P. Du, T. Niu and W. Yang, A novel hybrid system based on a new proposed algorithm—multi-objective whale optimization algorithm for wind speed forecasting, Appl. Energy, 208 (2017) 344–360.
[13] Q. Shakir kadhima, H. Kh. Obayes, M. H. Rashid, S. H. Abdul-zahrah and O. Khudhayer Obayes Features of molecules accumulation in the triplet state at excitation of the organic compounds by rectangular pulses, Organic Elect. 64 (2019) 202–204.
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Volume 12, Issue 2
November 2021Pages 603-607
- Receive Date: 08 March 2021
- Revise Date: 12 May 2021
- Accept Date: 23 May 2021