Аннотации:
© Springer International Publishing AG 2017. This paper presents a comparative study of several different systems for speech recognition for the Tatar language, including systems for very large and unlimited vocabularies. 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 with the sub-word based language model shows the best recognition result obtained on the test part of speech corpus.
