kaz29Вестник Казахстанско-Британского технического университетаHerald of the Kazakh-British Technical University1998-66882959-8109Казахстанско-Британский Технический Университет10.55452/1998-6688-2021-18-3-89-94kaz29-107Research ArticleФИЗИКО-МАТЕМАТИЧЕСКИЕ И ТЕХНИЧЕСКИЕ НАУКИPHYSICAL, MATHEMATICAL AND TECHNICAL SCIENCESОБЗОР: МЕТОДЫ АВТОМАТИЧЕСКОЙ РЕЧЕВОЙ СЕГМЕНТАЦИИA REVIEW: METHODS OF AUTOMATIC SPEECH SEGMENTATIONПакА. А.PakA. A.

050000, Алматы

050000, st. Pushkin 125b, Almaty

ЖумагелдыкызыА.ZhumageldikyzyA.

050000, Алматы

050000, st. Tole bi 59, Almaty

ЕрмековаН. С.ErmekovaN. S.

040000, Талдыкорган

040000, st. I. Zhansugurov 187a, Taldykorgan

Институт Информационных и Вычислительных технологийКазахстанInstitute of Information and Computational technologiesKazakhstanКазахстанско-Британский технический университетКазахстанKazakh-British technical universityKazakhstanЖетысуский университет имени И.ЖансугуроваКазахстанZhetysu university named after I.ZhansugurovKazakhstan2021051120211838994Copyright © Пак А.А., Жумагелдыкызы А., Ермекова Н.С., 20212021Пак А.А., Жумагелдыкызы А., Ермекова Н.С.Pak A.A., Zhumageldikyzy A., Ermekova N.S.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://vestnik.kbtu.edu.kz/jour/article/view/107

Сегментация - это процесс разделения речевого сигнала на основные языковые единицы. Сегментация речевых сигналов - одна из важнейших задач в системах автоматической обработки речи. В данной статье предлагается обзор методов автоматической сегментации речи. Кроме того рассматриваются методы преобразований вейвлетов и Гильберта-Хуанга, а также техники, основанные на скрытых Марковских моделях.

Segmentation is a process of dividing a speech signal into the basic units of language. Segmentation of the speech signals is one of the most important tasks in automatic speech processing systems. This paper proposes a review of methods of automatic speech segmentation. Moreover, methods of wavelet and Hilbert-Huang transformations and techniques based on hidden Markov models are considered.

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The authors declare that there are no conflicts of interest present.