MODERN TRENDS IN THE DEVELOPMENT OF SPEECH RECOGNITION SYSTEMS - Mamyrbayev, O.; Oralbekova, D. (Academic Scientific Journal of Computer Science, 2020)
This article presents the main ideas, advantages and disadvantages of models based on hidden Markov models (HMMs) - a Gaussian mixture models (GMM), end-to-end models and indicates that the end-to-end model is a developing area in the field of speech recognition. A review of studies that conducted in this subject area shows that end-to-end speech recognition systems can achieve results comparable to the results of standard systems using hidden Markov models, but using a simpler configuration and faster operation of the recognition system both in training and in decoding. An analytical review of the varieties of end-to-end systems for automatic speech recognition is considered, namely, models based on the connection time classification (CTC), attention-based mechanism and conditional random fields (CRF), and theoretical comparisons are made. Ultimately, their respective advantages and disadvantages and the possible future development of these systems are indicated.