Transfer Learning of Transformer-Based Speech Recognition Models from Czech to Slovak

Author:

Lehečka JanORCID,Psutka Josef V.ORCID,Psutka JosefORCID

Publisher

Springer Nature Switzerland

Reference17 articles.

1. Ardila, R., et al.: Common voice: a massively-multilingual speech corpus. In: Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020), pp. 4211–4215 (2020)

2. Babu, A., et al.: XLS-R: self-supervised cross-lingual speech representation learning at scale. In: Proceedings of Interspeech 2022, pp. 2278–2282 (2022). https://doi.org/10.21437/Interspeech.2022-143

3. Baevski, A., Zhou, Y., Mohamed, A., Auli, M.: Wav2Vec 2.0: a framework for self-supervised learning of speech representations. In: Advances in Neural Information Processing Systems, vol. 33, pp. 12449–12460 (2020)

4. Graves, A., Fernández, S., Gomez, F., Schmidhuber, J.: Connectionist temporal classification: labelling unsegmented sequence data with recurrent neural networks. In: Proceedings of the 23rd International Conference on Machine Learning, pp. 369–376 (2006)

5. Heafield, K.: KenLM: faster and smaller language model queries. In: Proceedings of the Sixth Workshop on Statistical Machine Translation, pp. 187–197 (2011)

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