Analysis of Automatic Speech Recognition Methods

Iosifova, Olena and Iosifov, Ievgen and Sokolov, V. Y. and Romanovskyi, O. and Sukaylo, I. (2021) Analysis of Automatic Speech Recognition Methods Cybersecurity Providing in Information and Telecommunication Systems, 2923. pp. 252-257. ISSN 1613-0073

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Abstract

This paper outlines structures of different automatic speech recognition systems, hybrid and end-to-end, pros and cons for each of them, including the comparison of training data and computational resources requirements. Three main approaches to speech recognition are considered: hybrid Hidden Markov Model – Deep Neural Network, end-to-end Connectionist Temporal Classification and Sequence-to-Sequence. The Listen, Attend, and Spell approach is chosen as an example for the Sequence-to-Sequence model.

Item Type:	Article
Additional Information:	EID: 2-s2.0-85112360373
Uncontrolled Keywords:	Automatic speech recognition; ASR; hidden Markov model; HMM; deep neural network; DNN; LAS; hybrid; end-to-end; sequence-to-sequence; speech recognition; speech-to-text
Subjects:	Це архівна тематика Київського університету імені Бориса Грінченка > Статті у наукометричних базах > Scopus
Divisions:	Це архівні підрозділи Київського університету імені Бориса Грінченка > Факультет інформаційних технологій та математики > Кафедра інформаційної та кібернетичної безпеки імені професора Володимира Бурячка
Depositing User:	Volodymyr Sokolov
Date Deposited:	20 Aug 2021 11:58
Last Modified:	27 Aug 2021 06:20
URI:	https://elibrary.kubg.edu.ua/id/eprint/36995

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