Recent Advances in Robust Speech Recognition Technology


Javier Ramírez, Juan Manuel Górriz

DOI: 10.2174/9781608051724111010
eISBN: 978-1-60805-172-4, 2011
ISBN: 978-1-60805-389-6

Indexed in: Scopus, EBSCO.

This E-book is a collection of articles that describe advances in speech recognition technology. Robustness in speech recognition refe...[view complete introduction]
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Robust Large Vocabulary Continuous Speech Recognition Based on Missing Feature Techniques

- Pp. 141-154 (14)

Yujun Wang, Maarten Van Segbroeck and Hugo Van hamme


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.

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