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Robust Speech Recognition using Adaptive Noise Cancellation.

Author(s)
M. WAQAS Department of Computer Systems Engineering, University of Engineering and Technology, Peshawar, Pakistan
M. A. A. KHAN Department of Computer Systems Engineering, University of Engineering and Technology, Peshawar, Pakistan
M. NAEEM Department of Computer Science, University of Peshawar, Pakistan
N. AHMAD Department of Computer Systems Engineering, University of Engineering and Technology, Peshawar, Pakistan
A. GUL Department of Statistics, Shaheed Benazir Bhutto Women University, Peshawar, Pakistan
Abstract
This paper introduces the adaptive noise cancellation technique for the noise reduction in Robust Automatic Speech Recognition. The adaptive noise cancellation is used as front-end stage to enhance the extracted features for speech recognition under noisy conditions. More specifically, the Constrained Stability Least Mean Square (CS-LMS) algorithm which is a member of the family of adaptive filters has been applied. The Hidden Markov Model based Tool Kit (HTK) is used for training and testing the Automatic Speech Recognizer system. The result obtained shows that the application of adoptive filtering at the front-end enhances the performance of the system in noisy conditions while the CS-LMS algorithm gives the most superior performance among the family of LMS algorithms.
Publication Details
Page(s) 895-898
DOI DOI not available
Published Journal: Sindh University Research Journal, Volume: 49, Issue: 4, Year: 2017

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Keywords
Robust Speech Recognition, automatic speech recognition
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