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2022 | OriginalPaper | Buchkapitel

Comparison of Modelling ASR System with Different Features Extraction Methods Using Sequential Model

verfasst von : Aishwarya Suresh, Anushka Jain, Kriti Mathur, Pooja Gambhir

Erschienen in: Artificial Intelligence and Speech Technology

Verlag: Springer International Publishing

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Abstract

Speech recognition refers to a device’s ability to respond to spoken instructions. Speech recognition facilitates hands-free use of various gadgets and appliances (a godsend for many incapacitated persons), as well as supplying input for automatic translation and ready-to-print dictation. Many industries, including healthcare, military telecommunications, and personal computing, use speech recognition programmes. In our paper, we are including the comparison between the different feature extraction methods (BFCC, GFCC, MFCC, MFCC Delta, MFCC Double Delta, LFCC and NGCC) using neural networks.

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Vorheriges Kapitel Hindi Phoneme Recognition - A Review

Nächstes Kapitel Latest Trends in Deep Learning for Automatic Speech Recognition System

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Titel: Comparison of Modelling ASR System with Different Features Extraction Methods Using Sequential Model
verfasst von: Aishwarya Suresh
Anushka Jain
Kriti Mathur
Pooja Gambhir
Verlag: Springer International Publishing
Buch: Artificial Intelligence and Speech Technology
Print ISBN: 978-3-030-95710-0

Electronic ISBN: 978-3-030-95711-7

Copyright-Jahr: 2022
DOI: https://doi.org/10.1007/978-3-030-95711-7_5

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