Fast offline transformer‐based end‐to‐end automatic speech recognition for real‐world applications

Author:

Oh Yoo Rhee1ORCID,Park Kiyoung1,Park Jeon Gue1

Affiliation:

1. Artificial Intelligence Research Laboratory Electronics and Telecommunications Research Institute Daejeon Republic of Korea

Funder

Institute for Information and Communications Technology Promotion

Publisher

Wiley

Subject

Electrical and Electronic Engineering,General Computer Science,Electronic, Optical and Magnetic Materials

Reference50 articles.

1. Rank‐weighted reconstruction feature for a robust deep neural network‐based acoustic model

2. Speech Recognition Using Deep Neural Networks: A Systematic Review

3. J.Liet al. On the comparison of popular end‐to‐end models for large scale speech recognition in Proc. Conf. Int. Speech Commun. Assoc. (Shanghai China) Oct. 2020 pp. 1–5.

4. V.Roger J.Farinas andJ.Pinquier Deep neural networks for automatic speech processing: A survey from large corpora to limited data arXiv preprint CoRR 2020 arXiv: 2003.04241.

5. D.Bahdanau K.Cho andY.Bengio Neural machine translation by jointly learning to align and translate in Proc. Int. Conf. Learn. Represent. (San Diego CA USA) May 2015.

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