Enhancing Performance of End-to-End Gujarati Language ASR using combination of Integrated Feature Extraction and Improved Spell Corrector Algorithm

Enhancing Performance of End-to-End Gujarati Language ASR using combination of Integrated Feature Extraction and Improved Spell Corrector Algorithm

A number of intricate deep learning architectures for effective End-to-End (E2E) speech recognition systems have emerged due to recent advancements in algorithms and technical resources. The proposed work develops an ASR system for the publicly accessible dataset on Gujarati language. The approach p...

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Bibliographic Details
Main Authors: Bhagat Bhavesh, Dua Mohit
Format: Article
Language:English
Published: EDP Sciences 2023-01-01
Series:ITM Web of Conferences
Subjects:
asr
mfcc
cqcc
spell corrector
bidirectional encoder representations from transformers (bert)
deepspeech2 model
Online Access:https://www.itm-conferences.org/articles/itmconf/pdf/2023/04/itmconf_I3cs2023_01016.pdf

Internet

https://www.itm-conferences.org/articles/itmconf/pdf/2023/04/itmconf_I3cs2023_01016.pdf

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