Scientific and analytical journal «Vestnik Saint-Petersburg university of State fire service of EMERCOM of Russia» Scientific and analytical journal «Vestnik Saint-Petersburg university of State fire service of EMERCOM of Russia» Научно-аналитический журнал "Вестник Санкт-Петербургского университета ГПС МЧС России" 2218-130X 65968 ТРУДЫ МОЛОДЫХ УЧЕНЫХ WORKS OF YOUNG SCIENTISTS ТРУДЫ МОЛОДЫХ УЧЕНЫХ AUTOMATIC SPEECH RECOGNITION SYSTEMS FOR ARABIC SPEECH AND YEMENI DIALECT СИСТЕМЫ АВТОМАТИЧЕСКОГО РАСПОЗНАВАНИЯ АРАБСКОЙ РЕЧИ И ЙЕМЕНСКОГО ДИАЛЕКТА Радан Наим Хусейн Radan Naim Hussein naeem.radan@gmail.com Тверской государственный университет Tver Stare University 07 07 2023 07 07 2023 2023 2 194 212 14 04 2023 29 04 2023 https://journals.igps.ru/en/nauka/article/65968/view

Статья посвящена анализу научно-исследовательских работ по системам автоматического распознавания речи арабского языка и системам автоматического распознавания речи основных диалектов арабского мира. Существует несколько методов реализации систем распознавания речи. Одними из новых методов являются использование нейронных сетей и скрытых Марковских моделей, применяемых для распознавания речи. Арабский язык является одним из самых распространенных языков и наименее исследуемым с точки зрения распознавания речи. Данная статья представляет собой краткий обзор по имеющимся исследованиям в области распознавания арабской речи и арабского йеменского диалекта. В работе проанализированы наборы инструментов, доступные для разработки систем распознавания арабской речи. Приведены методики и алгоритмы, использованные для классификации и идентификации арабских диалектов. На текущий момент систем автоматического распознавания речи йеменского диалекта разработано относительно мало по сравнению с системами автоматического распознавания речи для современного стандартного арабского языка и системами автоматического распознавания речи других арабских диалектов.

The article is devoted to the analysis of research works on automatic speech recognition systems of the Arabic language and automatic speech recognition systems of the main dialects of the Arab world. There are several methods for implementing speech recognition systems. One of the new methods is the use of neural networks and hidden Markov models used for speech recognition. Arabic is one of the most widely spoken languages and one of the least researched in terms of speech recognition. This article is a brief overview of the available research in the field of Arabic speech recognition and the arabic yemeni dialect. The paper analyzes the sets of tools available for the development of Arabic speech recognition systems. The methods and algorithms used for the classification and identification of Arabic dialects are given. To date, there has been relatively little development of automatic speech recognition systems for Yemeni dialect compared to automatic speech recognition systems for modern standard arabic and automatic speech recognition systems for other arabic dialects.

 распознавание речи распознавание арабской речи арабский йеменский диалект нейронные сети скрытые Марковские модели идентификация диалектов классификация диалектов speech recognition arabic speech recognition arabic yemeni dialect neural networks hidden Markov models dialect identification dialect classification

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