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2020 | OriginalPaper | Buchkapitel

Development of a Tangent Based Robust Speech Feature Extraction Model

verfasst von : Mohammad Tareq Hosain, Abdullah Al Arif, Ahmed Iqbal Pritom, Md Rashedur Rahman, Md. Zahidul Islam

Erschienen in: Cyber Security and Computer Science

Verlag: Springer International Publishing

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Abstract

An accurate speech recognition system requires close observation of the selection of an error-free speech feature extraction model. This paper describes a prominent solution to obtain robust features from the sound spectrum and ensures the easy recognition of speech. The proposed architecture uses Tangent based (TB) auditory feature extraction that aims to find and process robust features from the sine wave of auditory signal data. This experiment suggests that every specific tune carries distinguishing signal patterns in the spectrum diagram and hence does the tangent of the amplitude of the same signal. To recognize the sound, a single attribute had been used rather than using multiple attributes where the slope of the sound spectrum being calculated.

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Titel: Development of a Tangent Based Robust Speech Feature Extraction Model
verfasst von: Mohammad Tareq Hosain
Abdullah Al Arif
Ahmed Iqbal Pritom
Md Rashedur Rahman
Md. Zahidul Islam
Verlag: Springer International Publishing
Buch: Cyber Security and Computer Science
Print ISBN: 978-3-030-52855-3

Electronic ISBN: 978-3-030-52856-0

Copyright-Jahr: 2020
DOI: https://doi.org/10.1007/978-3-030-52856-0_33

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