A comparative study of different filters for speech signals

Speech signal processing is one of the most quickly increasing domains of information science study, as well as a very active and popular research subject with significant academic and practical value. Voice signal processing research is vital to the disciplines of machine language, speech recognition, and speech synthesis, among others. With its strong computer capability, MATLAB software can easily finish the processing of voice signals. MATLAB may be used to analyze digitalized speech signals in the time and frequency domain, display time and frequency domain curves of speech signals, and analyze speech based on its properties. This study evaluates the impact of various filters on speech signal processing to help us better create speech coding, voice recognition, speech synthesis, and other approaches. It is based on a series of characterization and processing of speech signals using MATLAB software.

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A comparative study of different filters for speech signals

Semantic Scholar · Computer Science · 2022

Abstract

Speech signal processing is one of the most quickly increasing domains of information science study, as well as a very active and popular research subject with significant academic and practical value. Voice signal processing research is vital to the disciplines of machine language, speech recognition, and speech synthesis, among others. With its strong computer capability, MATLAB software can easily finish the processing of voice signals. MATLAB may be used to analyze digitalized speech signals in the time and frequency domain, display time and frequency domain curves of speech signals, and analyze speech based on its properties. This study evaluates the impact of various filters on speech signal processing to help us better create speech coding, voice recognition, speech synthesis, and other approaches. It is based on a series of characterization and processing of speech signals using MATLAB software.

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