Hybrid end-to-end model for Kazakh speech recognition

Mamyrbayev O.Z. Oralbekova D.O. Alimhan K. Nuranbayeva B.M.
July 2023 Springer

International Journal of Speech Technology
2023 #26 Issue 2 261 - 270 pp.

Modern automatic speech recognition systems based on end-to-end (E2E) models show good results in terms of the accuracy of language recognition, which have large corpuses for several thousand hours of speech for system training. Such models require a very large amount of training data, which is problematic for low-resource languages like the Kazakh language. However, many studies have shown that the combination of connectionist temporal classification with other E2E models improves the performance of systems even with limited training data. In this regard, the speech corpus of the Kazakh language was assembled, and this corpus was expanded using the augmentation method. Our work presents the implementation of a joint model of CTC and the attention mechanism for recognition of Kazakh speech, which solves the problem of rapid decoding and training of the system. The results demonstrated that the proposed E2E model using language models improved the system performance and showed the best result on our dataset for the Kazakh language. As a result of the experiment, the system achieved competitive results in Kazakh speech recognition.

Attention , Automatic speech recognition , Connectionist temporal classification , End-to-end , Low resource language

Text of the article Перейти на текст статьи

Institute of Information and Computational Technologies CS MES RK, 28 Shevchenko Str., Almaty, Kazakhstan
Satbayev University, Almaty, Kazakhstan
Al-Farabi Kazakh National University, Almaty, Kazakhstan
L.N. Gumilyov Eurasian National University, Satpayev Str., 2, Nur-Sultan, 010008, Kazakhstan
Caspian University, Dostyk 85A, Almaty, Kazakhstan

Institute of Information and Computational Technologies CS MES RK
Satbayev University
Al-Farabi Kazakh National University
L.N. Gumilyov Eurasian National University
Caspian University

10 лет помогаем публиковать статьи Международный издатель

Книга Публикация научной статьи Волощук 2026 Book Publication of a scientific article 2026