Corpus ID: 227231791

Team_Swift at SemEval-2020 Task 9: Tiny Data Specialists through Domain-Specific Pre-training on Code-Mixed Data

@inproceedings{Malte2020Team_SwiftAS,
  title={Team_Swift at SemEval-2020 Task 9: Tiny Data Specialists through Domain-Specific Pre-training on Code-Mixed Data},
  author={Aditya Malte and P. Bhavsar and Sushant Rathi},
  booktitle={SemEval@COLING},
  year={2020}
}

Aditya Malte, P. Bhavsar, Sushant Rathi

Published in SemEval@COLING 2020

Computer Science

Code-mixing is an interesting phenomenon where the speaker switches between two or more languages in the same text. In this paper, we describe an unconventional approach to tackling the SentiMix Hindi-English challenge (uid: aditya_malte). Instead of directly fine-tuning large contemporary Transformer models, we train our own domain-specific embeddings and use them for downstream tasks. We also discuss how this technique provides comparable performance while making for a much more deployable… CONTINUE READING

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