Large vocabulary continuous speech recognition for Urdu

Authors:
Huda Sarfraz;Sarmad Hussain;Riffat Bokhari;Agha Ali Raza;Inam Ullah;Zahid Sarfraz;Sophia Pervez;Asad Mustafa;Iqra Javed;Rahila Parveen
Affiliations:
University of Engineering and Technology, Lahore, Pakistan;University of Engineering and Technology, Lahore, Pakistan;National University of Computer and Emerging Sciences, Lahore, Pakistan;National University of Computer and Emerging Sciences, Lahore, Pakistan;University of Engineering and Technology, Lahore, Pakistan;National University of Computer and Emerging Sciences, Lahore, Pakistan;National University of Computer and Emerging Sciences, Lahore, Pakistan;University of Engineering and Technology, Lahore, Pakistan;University of Engineering and Technology, Lahore, Pakistan;University of Engineering and Technology, Lahore, Pakistan
Venue:
Proceedings of the 8th International Conference on Frontiers of Information Technology
Year:
2010

Citing 5
Cited 0

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Abstract

This paper presents the development of acoustic and language models for robust Urdu speech recognition using the CMU Sphinx Open Source Toolkit for speech recognition. Three models have been developed incrementally, with the addition of speech data of up to two speakers per pass; one model using data from 40 female speakers only, one from 41 male speakers only, and one with both male and female speakers (81 speakers). This paper presents the current recognition results, and discusses approaches for improving these recognition rates.