Applications of Deep Learning Approaches in Speech Recognition: A Survey-Reference-Cited by-同舟云学术

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Applications of Deep Learning Approaches in Speech Recognition: A Survey

Published:2022 Issue: Volume: Page:189-196
ISSN:2367-3370
Container-title:Proceedings of International Conference on Computing and Communication Networks
language:
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Author:

Ali Al-Janabi Sameer I.,Lateef Ali Azawii Abdul

Publisher

Springer Nature Singapore

Link

https://link.springer.com/content/pdf/10.1007/978-981-19-0604-6_17

Reference17 articles.

1. A. Kumar, S. Verma, H. Mangla, A survey of deep learning techniques in speech recognition, in Proceedings of IEEE 2018 International Conference on Advances in Computing, Communication Control and Networking, ICACCCN 2018 (2018), pp. 179–185

2. E. Trentin, M. Gori, A survey of hybrid ANN/HMM models for automatic speech recognition. Neurocomputing 37(1–4), 91–126 (2001)

3. L. Deng, X. Li, Machine learning paradigms for speech recognition: an overview. IEEE Trans. Audio Speech Lang. Process. 21(5), 1060–1089 (2013)

4. H. Bourlard, N. Morgan, Connectionist Speech Recognition—A Hybrid Approach (1994)

5. S. Malla, A. Alsadoon, S.K. Bajaj, A DFC taxonomy of speech emotion recognition based on convolutional neural network from speech signal, in CITISIA 2020—IEEE Conference on Innovative Technologies in Intelligent Systems and Industrial Applications, Proceedings (2020)

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1. Human Voice Recognition for Subtitle Generators on Khmer and Vietnamese Newsletter Videos;2022 RIVF International Conference on Computing and Communication Technologies (RIVF);2022-12-20

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