Small and large vocabulary speech recognition of MP3 data under real-word conditions: Experimental study

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Abstract

This paper presents the study of speech recognition accuracy both for small and large vocabulary task with respect to different levels of MP3 compression of processed data. The motivation behind the work was to evaluate the usage of ASR system for off-line automatic transcription of recordings collected from standard present MP3 devices under different levels of background noise and channel distortion. Although MP3 may not be an optimal compression algorithm, the performed experiments have prooved that it does not distort speech signal significantly for higher compression rates. Realized experiments showed also that the accuracy of speech recognition (both small- and large-vocabulary) decreased very slowly for the bit-rate of 24 kbps and higher. However, slightly different setup of speech feature computation is necessary for MP3 speech data, mainly PLP features give significantly better results in comparison to MFCC. © Springer-Verlag Berlin Heidelberg 2012.

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Pollak, P., & Borsky, M. (2012). Small and large vocabulary speech recognition of MP3 data under real-word conditions: Experimental study. In Communications in Computer and Information Science (Vol. 314, pp. 409–419). https://doi.org/10.1007/978-3-642-35755-8_29

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