Abstract
Multilingual writers and speakers often alternate between two languages in a single discourse. This practice is called “code-switching”. Existing sentiment detection methods are usually trained on sentiment-labeled monolingual text. Manually labeled code-switched text, especially involving minority languages, is extremely rare. Consequently, the best monolingual methods perform relatively poorly on code-switched text. We present an effective technique for synthesizing labeled code-switched text from labeled monolingual text, which is relatively readily available. The idea is to replace carefully selected subtrees of constituency parses of sentences in the resource-rich language with suitable token spans selected from automatic translations to the resource-poor language. By augmenting the scarce labeled code-switched text with plentiful synthetic labeled code-switched text, we achieve significant improvements in sentiment labeling accuracy (1.5%, 5.11% 7.20%) for three different language pairs (English-Hindi, English-Spanish and English-Bengali). The improvement is even significant in hatespeech detection whereby we achieve a 4% improvement using only synthetic code-switched data (6% with data augmentation).- Anthology ID:
- P19-1343
- Volume:
- Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
- Month:
- July
- Year:
- 2019
- Address:
- Florence, Italy
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 3528–3537
- Language:
- URL:
- https://aclanthology.org/P19-1343
- DOI:
- 10.18653/v1/P19-1343
- Cite (ACL):
- Bidisha Samanta, Niloy Ganguly, and Soumen Chakrabarti. 2019. Improved Sentiment Detection via Label Transfer from Monolingual to Synthetic Code-Switched Text. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 3528–3537, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- Improved Sentiment Detection via Label Transfer from Monolingual to Synthetic Code-Switched Text (Samanta et al., ACL 2019)
- PDF:
- https://preview.aclanthology.org/paclic-22-ingestion/P19-1343.pdf
- Code
- bidishasamantakgp/2019_CSGen_ACL