End-to-End Multi-dialect Malayalam Speech Recognition Using Deep-CNN, LSTM-RNN, and Machine Learning Approaches
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-0609-3_3
Reference12 articles.
1. Yang C-HH et al (2021) Decentralizing feature extraction with quantum convolutional neural network for automatic speech recognition. In: ICASSP 2021—2021 IEEE international conference on acoustics, speech, and signal processing (ICASSP), pp 6523–6527. https://doi.org/10.1109/ICASSP39728.2021.9413453
2. Zhu Q-S, Zhang J, Zhang Z-Q, Wu M-H, Fang X, Dai L-R (2022) A noise-robust self-supervised pre-training model based speech representation learning for automatic speech recognition. In: ICASSP 2022—2022 IEEE international conference on acoustics, speech and signal processing (ICASSP), pp 3174–3178. https://doi.org/10.1109/ICASSP43922.2022.9747379
3. Hamed I, Denisov P, Li C-Y, Elmahdy M, Abdennadher S, Vu NT (2022) Investigations on speech recognition systems for low-resource dialectal Arabic–English code-switching speech. Comput Speech Lang 72:101278. ISSN 0885-2308. https://doi.org/10.1016/j.csl.2021.101278
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