Artificial Neural Networks Combined with the Principal Component Analysis for Non-Fluent Speech Recognition.
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SUBMITTER: Swietlicka I
PROVIDER: S-EPMC8749906 | biostudies-literature | 2022 Jan
REPOSITORIES: biostudies-literature
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Artificial Neural Networks Combined with the Principal Component Analysis for Non-Fluent Speech Recognition.
Świetlicka Izabela I Kuniszyk-Jóźkowiak Wiesława W Świetlicki Michał M
Sensors (Basel, Switzerland) 20220101 1
The presented paper introduces principal component analysis application for dimensionality reduction of variables describing speech signal and applicability of obtained results for the disturbed and fluent speech recognition process. A set of fluent speech signals and three speech disturbances-blocks before words starting with plosives, syllable repetitions, and sound-initial prolongations-was transformed using principal component analysis. The result was a model containing four principal compon ...[more]
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