Improving data augmentation for low resource speech-to-text translation with diverse paraphrasing.
- DOI
- 10.1016/j.neunet.2022.01.016
- Published
- 2022 Apr
- Container
- Neural networks : the official journal of the International Neural Network Society
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.neunet.2022.01.016,
title = {Improving data augmentation for low resource speech-to-text translation with diverse paraphrasing.},
author = {Mi C and Xie L and Zhang Y},
year = {2022},
journal = {Neural networks : the official journal of the International Neural Network Society},
doi = {10.1016/j.neunet.2022.01.016},
url = {https://doi.org/10.1016/j.neunet.2022.01.016}
}RIS
TY - JOUR TI - Improving data augmentation for low resource speech-to-text translation with diverse paraphrasing. AU - Mi C AU - Xie L AU - Zhang Y PY - 2022 JO - Neural networks : the official journal of the International Neural Network Society DO - 10.1016/j.neunet.2022.01.016 UR - https://doi.org/10.1016/j.neunet.2022.01.016 ER -
APA
C, M., L, X., & Y, Z. (2022). Improving data augmentation for low resource speech-to-text translation with diverse paraphrasing.. Neural networks : the official journal of the International Neural Network Society. https://doi.org/10.1016/j.neunet.2022.01.016
Source records
- pubmed · retrieved 2026-09-26T23:53:20.013Z