Abstract
Speaker Adaptation is a technique which is used to improve the recognition accuracy of Automatic Speech Recognition (ASR) systems. Here, we report a study of the impact of online speaker adaptation on the performance of a speaker independent, continuous speech recognition system for Hindi language. The speaker adaptation is performed using the Maximum Likelihood Linear Regression (MLLR) transformation approach. The ASR system was trained using narrowband speech. The efficacy of the speaker adaptation is studied by using an unrelated speech database. The MLLR transform based speaker adaptation technique is found to significantly improve the accuracy of the Hindi ASR system by 3%.
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© 2011 Springer-Verlag Berlin Heidelberg
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Sivaraman, G., Mehta, S., Nabar, N., Samudravijaya, K. (2011). Higher Accuracy of Hindi Speech Recognition Due to Online Speaker Adaptation. In: Shah, K., Lakshmi Gorty, V.R., Phirke, A. (eds) Technology Systems and Management. Communications in Computer and Information Science, vol 145. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20209-4_33
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DOI: https://doi.org/10.1007/978-3-642-20209-4_33
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-20208-7
Online ISBN: 978-3-642-20209-4
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