Chapter 9

Robust Large Vocabulary Continuous Speech Recognition Based on Missing Feature Techniques

Yujun Wang, Maarten Van Segbroeck and Hugo Van hamme

Abstract

Solutions for two important problems for the deployment of noise-robust large vocabulary automatic speech recognizers using the missing data paradigm are presented. irst problem is the generation of missing data masks. We propose and evaluate a method based on vector quantization and harmonicity that successfully exploits the characteristics of speech while requiring only weak assumptions on the noise. A second problem that is addressed is computational efficiency. We advocate the usage of PROSPECT features and the L-cluster-Mbest method for Gaussian selection. In total, a speed up of a factor of about 6 can be achieved with these methods.

Total Pages: 141-154 (14)

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