Sub-band Information Fusion Based on Wavelet Thresholding for Robust Speech Recognition

Subject Areas : Journal of Computer & Robotics

Babak  Nasersharif ¹ (School of Computer Engineering, Faculty of Engineering, University of Guilan, Rasht, Iran Audio and Speech Processing Lab, Department of Computer Engineering, Iran university of Science and technology, Tehran, Iran)
Ahamd  Akbari ² (Audio and Speech Processing Lab, Department of Computer Engineering, Iran university of Science and technology, Tehran, Iran)

Received: 2010-01-24 Accepted : 2010-06-05 Published : 2012-06-12

Keywords: Recognition, Wavelet, Sub-band, Likelihood Combination,

Abstract :

In recent years, sub-band speech recognition has been found useful in addressing the need for robustness in speech recognition, especially for the speech contaminated by band-limited noise. In sub-band speech recognition, the full band speech is divided into several frequency sub-bands, with the result of the recognition task given by the combination of the sub-band feature vectors or their likelihoods as generated by the corresponding sub-band recognizers. In this paper, we draw on the notion of discrete wavelet transform to divide the speech signal into sub-bands. We also make use of the robust features in sub-bands in order to obtain a higher sub-band speech recognition rate. In addition, we propose a likelihood weighting and fusion method based on the wavelet thresholding technique. The experimental results indicate that the proposed weighting methods for likelihood combination and classifiers fusion improve the sub-band speech recognition rate in noisy conditions.

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