Language Identification of Hindi-English tweets using code-mixed BERT

• URL: http://arxiv.org/abs/2107.01202v1
• Date: Fri, 2 Jul 2021 17:51:36 GMT
• Title: Language Identification of Hindi-English tweets using code-mixed BERT
• Authors: Mohd Zeeshan Ansari, M M Sufyan Beg, Tanvir Ahmad, Mohd Jazib Khan, Ghazali Wasim
• Abstract summary: The work utilizes a data collection of Hindi-English-Urdu codemixed text for language pre-training and Hindi-English codemixed for subsequent word-level language classification. The results show that the representations pre-trained over codemixed data produce better results by their monolingual counterpart.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: Language identification of social media text has been an interesting problem of study in recent years. Social media messages are predominantly in code mixed in non-English speaking states. Prior knowledge by pre-training contextual embeddings have shown state of the art results for a range of downstream tasks. Recently, models such as BERT have shown that using a large amount of unlabeled data, the pretrained language models are even more beneficial for learning common language representations. Extensive experiments exploiting transfer learning and fine-tuning BERT models to identify language on Twitter are presented in this paper. The work utilizes a data collection of Hindi-English-Urdu codemixed text for language pre-training and Hindi-English codemixed for subsequent word-level language classification. The results show that the representations pre-trained over codemixed data produce better results by their monolingual counterpart.

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