Uma B.V.

Work place: Department of Electronics & Communication, R.V. College of Engineering, Bengaluru, India



Research Interests: Image Processing, Image Compression, Computer systems and computational processes


Uma B. V. has obtained her M.E. in Digital Tech. & Instrumentation in 1995 and Ph.D. from Visveswaraya Technology University, Karnataka in 2009. Currently, she is working as Professor & Associate Dean in the Dept. of Electronics & Communication Engg., at R.V. College of Engineering, Bengaluru, India. She has published 30 papers in national, international conferences and journals. Her areas of interests are in the field of signal processing, broadband communication, underwater video compression and signal integrity in high-speed VLSI circuit. She is also working in the area of thin film transistor for flexible electronics. Executed project on video compression funded by DRDO, India.

Author Articles
Dominant Frequency Enhancement of Speech Signal to Improve Intelligibility and Quality

By Premananda B.S. Uma B.V.

DOI:, Pub. Date: 8 May 2015

In mobile devices, perceived speech signal deteriorates significantly in the presence of near-end noise as the signal arrives directly at the listener's ears in a noisy environment. There is an inherent need to increase the clarity and quality of the received speech signal in noisier environment. It is accomplished by incorporating speech enhancement algorithms at the receiver end. The objective is to improve the intelligibility and quality of the speech signal by dynamically enhancing the speech signal when the near-end noise dominates. This paper proposes a speech enhancement approaches by inculcating the threshold of hearing and auditory masking properties of the human ear. Incorporating the masking properties, the speech samples that are audible can be obtained. In low SNR environments, selective audible samples can be enhanced to improve the clarity of the signal rather than enhancing every loud sample. Intelligibility and quality of the enhanced speech signal are measured using Speech Intelligibility Index and Perceptual Evaluation of Speech Quality. Experimental results connote the intelligibility and quality improvement of the speech signal with the proposed method over the unprocessed far-end speech signal. This approach is efficient in overcoming the deterioration of speech signals in a noisy environment.

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