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

Subject Areas : Journal of Computer & Robotics

Babak Nasersharif ¹ , Ahamd Akbari ²

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
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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