Feature extraction in speech recognition using linear predictive coding: An overview

Over the past years, advancements in speech processing have mostly been driven by DSP approaches. The speech interface was designed to convert speech input into a parametric form for further processing (Speech-to-Text) and the resulting text output to speech synthesis (Text-to-Speech). Feature extra...

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Veröffentlicht in:I-Manager's Journal on Digital Signal Processing Jg. 10; H. 2; S. 16
Hauptverfasser: D. Suja, Darling, Hinduja, J.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: Nagercoil iManager Publications 01.07.2022
Schlagworte:
Acoustics
Coding
Communication
Digital signal processors
Discriminant analysis
Eigenvectors
Engineering
Feature extraction
Field programmable gate arrays
Methods
Principal components analysis
Signal processing
Speaking
Spectrum analysis
Speech
Speech processing
Speech recognition
Voice recognition
Waveforms
ISSN:2321-7480, 2322-0368
Online-Zugang:Volltext
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Zusammenfassung:Over the past years, advancements in speech processing have mostly been driven by DSP approaches. The speech interface was designed to convert speech input into a parametric form for further processing (Speech-to-Text) and the resulting text output to speech synthesis (Text-to-Speech). Feature extraction is done by changing the speech waveform into a parametric representation at a relatively low data rate so that it can be processed and analyzed later. There are numerous feature extraction techniques available. This paper presents the overview of Linear Predictive Coding (LPC).
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
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ISSN:2321-7480
2322-0368
DOI:10.26634/jdp.10.2.19289