Abstract
In the article we evaluate different techniques of acoustic modeling for speech recognition in the case of limited audio resources. The objective was to build different sets of acoustic models, the first was trained on a small set of telephone speech recordings and the other was trained on a bigger database with broadband speech recordings and later adapted to a different audio environment. Different adaptation methods (MLLR, MAP) were examined in combination with different parameterization features (MFCC, PLP, RPLP). We show that using adaptation methods, which are mainly used for speaker adaptation purposes, can increase the robustness of speech recognition in cases of mismatched training and working acoustic environment conditions.
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Gajšek, R., Žibert, J., Mihelič, F. (2008). Acoustic Modeling for Speech Recognition in Telephone Based Dialog System Using Limited Audio Resources. In: Sojka, P., Horák, A., Kopeček, I., Pala, K. (eds) Text, Speech and Dialogue. TSD 2008. Lecture Notes in Computer Science(), vol 5246. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-87391-4_40
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DOI: https://doi.org/10.1007/978-3-540-87391-4_40
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-87390-7
Online ISBN: 978-3-540-87391-4
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