Enhancing Language Identification in Indian Context Through Exploiting Learned Features with Wav2Vec2.0-Reference-Cited by-同舟云学术

Enhancing Language Identification in Indian Context Through Exploiting Learned Features with Wav2Vec2.0

Published:2023 Issue: Volume: Page:503-512
ISSN:0302-9743
Container-title:Speech and Computer
language:
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Author:

Gupta Shivang^ORCID,Motepalli Kowshik Siva Sai^ORCID,Kumar Ravi,Narasinga Vamsi^ORCID,Mirishkar Sai Ganesh^ORCID,Vuppala Anil Kumar^ORCID

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-48312-7_40

Reference21 articles.

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2. Balleda, J., Murthy, H.A., Nagarajan, T.: Language identification from short segments of speech. In: Sixth International Conference on Spoken Language Processing (2000)

3. Bartz, C., Herold, T., Yang, H., Meinel, C.: Language identification using deep convolutional recurrent neural networks. In: Liu, D., Xie, S., Li, Y., Zhao, D., El-Alfy, E.S.M. (eds.) Neural Information Processing, pp. 880–889. Springer International Publishing, Cham (2017). https://doi.org/10.1007/978-3-319-70136-3_93

4. Dehak, N., Torres-Carrasquillo, P.A., Reynolds, D., Dehak, R.: Language recognition via i-vectors and dimensionality reduction. In: Proceedings of INTERSPEECH (2011)

5. Diwan, A., et al.: MUCS 2021: multilingual and code-switching ASR challenges for low resource Indian languages. In: Interspeech 2021. ISCA (2021). https://doi.org/10.21437/interspeech.2021-1339

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