An Adaptive Learning Based Speech Enhancement Technique for Communication Systems

An Adaptive Learning Based Speech Enhancement Technique for Communication Systems
  IJETT-book-cover           
  
© 2021 by IJETT Journal
Volume-69 Issue-6
Year of Publication : 2021
Authors : Girika Jyoshna, Md Zia Ur Rahman
DOI :  10.14445/22315381/IJETT-V69I6P205

How to Cite?

Girika Jyoshna, Md Zia Ur Rahman, "An Adaptive Learning Based Speech Enhancement Technique for Communication Systems," International Journal of Engineering Trends and Technology, vol. 69, no. 6, pp. 31-37, 2021. Crossref, https://doi.org/10.14445/22315381/IJETT-V69I6P205

Abstract
Extraction of speech signal from contaminated signal is main task in all practical applications. While transmitting speech signal, many undesired components are added to desired speech signal and they are eliminated at destination by using adaptive algorithms. Conventional least mean square (LMS) algorithm is widely used because of its simplicity and robustness, step size is main parameter in this algorithm. If there is rapid increase in step size it will affect convergence rate and mean square error (MSE). There is a tradeoff between MSE and convergence. With variable step size, performance of algorithm is improved. Hence developed data variable, error variable, step variable and time variable based adaptive algorithms are proposed. Based on LMS, several adaptive noise elimination techniques are proposed and they are analyzed. In these algorithms step size is variable instead of constant step size and it is based on error signals at particular instant. By proposed algorithm it improves speech signal so that MSE is reduced further signal to noise ratio is also improved.

Keywords
Adaptive Learning, Adaptive noise cancellation, Normalization, Speech enhancement, Step size.

Reference
[1] J. Benesty, S. Makino, and J. D. Chen, Speech Enhancement. Berlin, Germany: Springer, (2005), ch. 1.
[2] P. C. Loizou, Speech Enhancement: Theory and Practice. Boca Raton, FL, USA: CRC Press, (2013), ch. 3.
[3] Nikolaos Dionelis, Mike Brookes, Member, Phase-Aware Single-Channel Speech Enhancement with Modulation-Domain Kalman Filtering, IEEE/ACM Transactions on Audio, Speech, and Language Processing, 26 (5) 2018.
[4] Jwu-Sheng Hu, Ming-Tang Lee, and Chia-Hsin Yang, Robust Adaptive Beam former for Speech Enhancement Using the Second-Order Extended Filter, IEEE transactions on audio, speech, and language processing, 21(1) (2013).
[5] Kais Khaldi, Abdel-Ouahab Boudraa, Monia Turki, Voiced/unvoiced speech classification-based adaptive filtering of decomposed empirical modes for speech enhancement, IET Signal Processing, (2015).
[6] Brady N. M. Laska, Miodrag Bolic´, and Rafik A. Goubran, Particle Filter Enhancement of Speech Spectral Amplitudes, IEEE transactions on audio, speech, and language processing, 18(8) (2010).
[7] B. Widrow and S. D. Stearns, Aduptiue Signal Processing. Englewood Cliffs, NJ: Prentice-Hall, (1985).
[8] S. Olmos, L. Sornmo and P. Laguna, Block adaptive filter with deterministic reference inputs for event-related signals:BLMS and BRLS, IEEE Trans. Signal Processing, 50 (2002) 1102-1112.
[9] Rizwan Ghaffar, Raymond Knopp, and Pin-Han Ho, Low Complexity BICM MIMOOFDM Demodulator, IEEE Transactions on Wireless Communications, 14(1) (2015) 558-569.
[10] Babu Sree Harsha P., Venkata Ratnam D, Fuzzy logic-based adaptive extended kalman filter algorithm for GNSS receivers,” Defence Science Journal, 68 (6) (2018) 560- 565.
[11] Vidya Sagar Y., Chaitresh K., Baba Eleyas Ahamad S., Tejaswi M, Validation of signals using principal component analysis, International Journal of Applied Engineering Research,12 (2017) 391-398.
[12] Suryanarayana G., Dhuli R, Super-Resolution Image Reconstruction Using Dual-Mode Complex Diffusion-Based Shock Filter and Singular Value Decomposition, Circuits, Systems, and Signal Processing, 36(8) (2017) 3409-3425.
[13] Parate P, Kanjalkar P, Compressive Sensing approach for data recovery from incomplete measurements for one dimensional signal, Proceedings of the 2016 2nd International Conference on Applied and Theoretical Computing and Communication Technology, iCATccT 2016 (2017) 686-691.
[14] Rao G.A., Syamala K., Kishore P.V.V., Sastry A.S.C.S, Deep convolutional neural networks for sign language recognition, 2018 Conference on Signal Processing And Communication Engineering Systems, SPACES 2018 (2018) 194- 197.
[15] Kumar E.K., Sastry A.S.C.S., Kishore P.V.V., Kumar M.T.K., Kumar D.A, Training CNNs for 3-D Sign Language Recognition with Color Texture Coded Joint Angular Displacement Maps, IEEE Signal Processing Letters, 25 (5) (2018) 645- 649.
[16] S. K. Gottapu and V. Appalaraju, Cognitive radio wireless sensor network localization in an open field, 2018 Conference on Signal Processing And Communication Engineering Systems (SPACES), Vijayawada , (2018) 45-48.
[17] Cheerla S., Ratnam D.V, RSS based Wi-Fi positioning method using multi layer neural networks, 2018 Conference on Signal Processing and Communication Engineering Systems, SPACES 2018 (2018) 58- 61.
[18] Cheerla S., Venkata Ratnam D., Teja Sri K.S., Sahithi P.S., Sowdamini G, Neural network based indoor localization using Wi-Fi received signal strength, Journal of Advanced Research in Dynamical and Control Systems, 10(4) (2018) 374- 379.
[19] Srivani I., Siva Vara Prasad G., Venkata Ratnam D, A Deep Learning-Based Approach to Forecast Ionospheric Delays for GPS Signals, IEEE Geoscience and Remote Sensing Letters, 16 (8) (2019) 1180-1184.
[20] Salman M.N., Trinatha Rao P., Ur Rahman M.Z, Adaptive noise cancellers for cardiac signal enhancement for IOT based health care systems, Journal of Theoretical and Applied Information Technology, 95 (10) (2017) 2206-2213.
[21] Putluri S., Ur Rahman M.Z., Fathima S.Y, Cloud-based adaptive exon prediction for DNA analysis, Healthcare Technology Letters, 5(1) (2018) 25- 30.
[22] Putluri S., Ur Rahman M.Z, Novel simplified logarithmic adaptive exon prediction for DNA analysis, Journal of Advanced Research in Dynamical and Control Systems, 10 (9 Special Issue) (2018) 1422- 1432.
[23] Sulthana A., Ur Rahman M.Z, Efficient adaptive noise cancellation techniques in an IOT Enabled Telecardiology System, International Journal of Engineering and Technology(UAE), 7 (2) (2018) 74- 78.
[24] Sulthana A., Rahman M.Z.U., Mirza S.S, An efficient kalman noise canceller for cardiac signal analysis in modern telecardiology systems, IEEE Access, 6 (2018) 34616- 34630.
[25] Gayathri N.B., Thumbur G., Rajesh Kumar P., Rahman M.Z.U., Reddy P.V., Lay-Ekuakille A, Efficient and Secure Pairing-Free Certificateless Aggregate Signature Scheme for Healthcare Wireless Medical Sensor Networks, IEEE Internet of Things Journal, 6(5) (2019) 9064-9075.
[26] N. Golyandina, V. Nekrutkin, and A. A. Zhigljavsky, Analysis of Time Series Structure: SSA and Related Techniques (Monographs on statistics and applied probability), vol. 90. Boca Raton, FL, USA: Chapman & Hall, 2001.
[27] S. Surekha, M. Z. Ur Rahman, A. Lay-Ekuakille, A. Pietrosanto and M. A. Ugwiri, Energy Detection for Spectrum Sensing in Medical Telemetry Networks using Modified NLMS algorithm, 2020 IEEE International Instrumentation and Measurement Technology Conference (I2MTC), Dubrovnik, Croatia, (2020) 1-5.
[28] Thumbur G., Gayathri N.B., Vasudeva Reddy P., Zia Ur Rahman M.D., Lay-Ekuakille A, Efficient pairing-free identity-based ADS-B authentication scheme with batch verification, IEEE Transactions on Aerospace and Electronic Systems, 55 (5) (2019) 2473-2486.
[29] Yasmin Fathima S., Zia Ur Rahman M., Krishna K.M., Bhanu S., Shahsavar M.S, Side Lobe Suppression in NC-OFDM Systems Using Variable Cancellation Basis Function, IEEE Access,5 (2017) 9415-9421.
[30] Gopisettryi G.K.D., VaddiKasulu K., Kamal K.R., Pranith G., Rahman M.Z.U, Significant node tracking effective reception networks using influential checkpoints, International Journal of Innovative Technology and Exploring Engineering, 8 (7) (2019) 57-60.
[31] Ik-Soo Ahn, Seong-Geon Bae, Myung-Jin Bae A Study on Risk Analysis and Prevention of the Noise Cancelling Earphone, International Journal of Engineering Trends and Technology 68(10) (2020) 24-27.
[32] Md. Zia Ur Rahman, S. Akanksha, R.P. Krishna Kalyan, S. Nayeem Energy Detection in Medical Telemetry Systems using Logarithmic Adaptive Algorithm, International Journal of Engineering Trends and Technology 68(9) (2020) 49-56.