Hybrid deep learning based automatic speech recognition model for recognizing non-Indian languages-Reference-Cited by-同舟云学术

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Hybrid deep learning based automatic speech recognition model for recognizing non-Indian languages

Published:2023-09-15 Issue: Volume: Page:
ISSN:1380-7501
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Gupta Astha,Kumar Rakesh^ORCID,Kumar Yogesh

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Link

https://link.springer.com/content/pdf/10.1007/s11042-023-16748-1.pdf

Reference44 articles.

1. Bhable S, Kayte C (2020) Review: Multilingual Acoustic modeling of Automatic Speech Recognition (ASR) for low resource languages. In IEEE International Conference on Advent Trends in Multidisciplinary Research and Innovation (ICATMRI).https://doi.org/10.1109/ICATMRI51801.2020.9398431

2. Malik M, Malik K, Mehmood K, Makhdoom I (2021) Automatic speech recognition: a survey. In Multimedia Tools and Applications, 9411–9457. https://doi.org/10.1007/s11042-020-10073-7.

3. Xiaohui Chu X (2021) Speech Recognition Method Based on Deep Learning and Its Application. In IEEE International Conference of Social Computing and Digital Economy (ICSCDE). https://doi.org/10.1109/ICSCDE54196.2021.00075

4. Kalhor E, Bakhtiari B (2021) Speaker independent feature selection for speech emotion recognition: A multi-task approach. In Multimedia Tools and Applications 80:8127–8146. https://doi.org/10.1007/s11042-020-10119-w

5. Guntur R, Ramakrishnan K, Mittal V (2021) Automatic Classification of Foreign Language Accent. In IEEE 2nd Global Conference for Advancement in Technology (GCAT). https://doi.org/10.1109/GCAT52182.2021.9587650

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