Abstract
This paper presents a comparative study of several different approaches to speech recognition for the Tatar language. All the compared systems use a corpus-based approach, so recent results in speech and text corpora creation are also shown. The recognition systems differ in acoustic modelling algorithms, basic acoustic units, and language modelling techniques. The DNN-based system shows the best recognition result obtained on the test part of speech corpus.
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CITATION STYLE
Khusainov, A. (2018). A comparative analysis of speech recognition systems for the tatar language. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10761 LNCS, pp. 515–523). Springer Verlag. https://doi.org/10.1007/978-3-319-77113-7_40
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