A Machine Learning Approach for Speech Detection in Modern Wireless Communication Environment

Authors

Keywords:

Wireless Communication, OFDM, Speech detection, RBFN, BER.

Abstract

Modern wireless communication has gained a improved position as compared to previous time. Similarly, speech communication is the major focus area of research in respective applications. Many developments are done in this field. In this work, we have chosen the OFDM modulation based communication system, as it has importance in both licensed and unlicensed wireless communication platform. The voice signal is passed though the proposed model to obtain at the receiver end. Due to different circumstances, the signal may be corrupted partially at the user end. Authors try to achieve a better signal for reception using a neural network model of RBFN. The parameters are chosen for the RBFN model, as energy, ZCR, ACF, and fundamental frequency of the speech signal. In one part these parameters have eligibility to eliminate noise partially, where as in other part the RBFN model with these parameters proves its efficacy for both noisy speech signals with noisy channel as Gaussian channel. The efficiency of OFDM model is verified in terms of symbol error rate and the transmitted speech signal is evaluated in term of SNR that shows the reduction of noise. For visual inspection, a sample of signal, noisy signal and received signal is also shown. The experiment is performed with 5dB, 10dB, 15dB noise levels. The result proves the performance of RBFN model as the filter.The performance is measured as the listener’s voice in each condition. The results show that, at the time of the voice in noise environment, proposed technique improves the intelligibility on speech quality.

Author Biographies

Shibanee Dash, RVR & JC College of Engineering Guntur, Andhra Pradesh, India

Shibanee Dash is presently working as a Assistant Professor  in the Department of Electronics and Communication Engineering, at R.V.R & J.C College of Engineering (Autonomous), Guntur, Andhra Pradesh, India. She has Master of Technology in Electronics and Telecommunication at Kalinga Institute of Industrial Technology (Deemed to be University), India. She has 3 year of experience in teaching and research

Mihir Narayan Mohanty, ITER, Siksha 'O' Anusandhan(Deemed to be University),Bhubaneswar, Odisha, India

Mihir Narayan Mohanty is presently working as a Professor in the Department of Electronics and Communication Engineering, Institute of Technical Education and Research. Siksha ‘O’ Anusandhan (Deemed to be University), Bhubaneswar, Odisha, India. He has published over 300 papers in International/National Journals and Conferences along with approximately 25 years of teaching experience. He is the active member of many professional societies like IEEE, IET, EMC & EMI Engineers India, ISCA, ACEEE, IAEng, CSI and also Fellow of IETE and IE (I). He has received his M.Tech. Degree in Communication System Engineering from the Sambalpur University, Sambalpur, Odisha and done his Ph.D. work in Applied Signal Processing. His area of research interests includes Applied Signal and image Processing, Digital Signal/Image Processing, Biomedical Signal Processing, Microwave Communication Engineering and Speech Processing.

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Published

2018-12-28

How to Cite

Dash, S., & Mohanty, M. N. (2018). A Machine Learning Approach for Speech Detection in Modern Wireless Communication Environment. International Journal of Machine Learning and Networked Collaborative Engineering, 2(04), 170–179. Retrieved from https://mlnce.net/index.php/Home/article/view/50

Issue

Vol. 2 No. 04 (2018): Volume No 02 Issue No 04

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Articles

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