Abstract
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.
Highlights
Research in the field of speech signal processing is an active progress
One of the most important tasks in automatic speech processing systems is the task of segmentation by the phonetic transcription of the language[7]
Digital processing methods imply the possibility of their use for solving problems of speech signal processing
Summary
Research in the field of speech signal processing is an active progress. Despite the high speed of computer technology and information technology development, the main problems of speech applications are still relevant. Түйінді сөздер: сөйлеу сигналдары, сөйлеуді сегментациялау, автоматты сегментациялау әдістері, дискретті вейвлет түрлендіру әдісі, Гильберт-Хуанг түрлендіруі, жасырын Марков модельдері. Ключевые слова: речевые сигналы, сегментация речи, методы автоматической сегментации, метод дискретного вейвлет-преобразования, преобразование Гильберта-Хуанга, скрытые Марковские модели.
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