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Please use this identifier to cite or link to this item: https://libeldoc.bsuir.by/handle/123456789/34756
Title: Spectrum estimation of speech: coding and feature extraction
Authors: Taha, M.
Azarov, E. S.
Таха, М.
Азаров, И. С.
Keywords: материалы конференций
linear prediction
speech coding
spectrum estimation
Issue Date: 2019
Publisher: БГУИР
Citation: Taha, M. Spectrum estimation of speech: coding and feature extraction / M. Taha, E. S. Azarov // BIG DATA and Advanced Analytics = BIG DATA и анализ высокого уровня : сборник материалов V Международной научно-практической конференции, Минск, 13–14 марта 2019 г. В 2 ч. Ч. 1 / Белорусский государственный университет информатики и радиоэлектроники; редкол. : В. А. Богуш [и др.]. – Минск, 2019. – С. 66 – 72.
Abstract: Speech analysis and spectrum estimation has been the fundamental problem of digital signal processing for recent decades. The problem still has a huge practical impact on modern speech processing applications that involve coding and deep learning. The paper reviews the main speech spectral estimation techniques including linear prediction and cepstrum.
URI: https://libeldoc.bsuir.by/handle/123456789/34756
Appears in Collections:BIG DATA and Advanced Analytics = BIG DATA и анализ высокого уровня (2019)

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