Abstract
This paper describes the models submitted by the team MUCS for “Hope Speech Detection for Equality, Diversity, and Inclusion-EACL 2021” shared task that aims at classifying a comment / post in English and code-mixed texts in two language pairs, namely, Tamil-English (Ta-En) and Malayalam-English (Ma-En) into one of the three predefined categories, namely, “Hope_speech”, “Non_hope_speech”, and “other_languages”. Three models namely, CoHope-ML, CoHope-NN, and CoHope-TL based on Ensemble of classifiers, Keras Neural Network (NN) and BiLSTM with Conv1d model respectively are proposed for the shared task. CoHope-ML, CoHope-NN models are trained on a feature set comprised of char sequences extracted from sentences combined with words for Ma-En and Ta-En code-mixed texts and a combination of word and char ngrams along with syntactic word ngrams for English text. CoHope-TL model consists of three major parts: training tokenizer, BERT Language Model (LM) training and then using pre-trained BERT LM as weights in BiLSTM-Conv1d model. Out of three proposed models, CoHope-ML model (best among our models) obtained 1st, 2nd, and 3rd ranks with weighted F1-scores of 0.85, 0.92, and 0.59 for Ma-En, English and Ta-En texts respectively.- Anthology ID:
- 2021.ltedi-1.27
- Volume:
- Proceedings of the First Workshop on Language Technology for Equality, Diversity and Inclusion
- Month:
- April
- Year:
- 2021
- Address:
- Kyiv
- Editors:
- Bharathi Raja Chakravarthi, John P. McCrae, Manel Zarrouk, Kalika Bali, Paul Buitelaar
- Venue:
- LTEDI
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 180–187
- Language:
- URL:
- https://preview.aclanthology.org/add_missing_videos/2021.ltedi-1.27/
- DOI:
- Cite (ACL):
- Fazlourrahman Balouchzahi, Aparna B K, and H L Shashirekha. 2021. MUCS@LT-EDI-EACL2021:CoHope-Hope Speech Detection for Equality, Diversity, and Inclusion in Code-Mixed Texts. In Proceedings of the First Workshop on Language Technology for Equality, Diversity and Inclusion, pages 180–187, Kyiv. Association for Computational Linguistics.
- Cite (Informal):
- MUCS@LT-EDI-EACL2021:CoHope-Hope Speech Detection for Equality, Diversity, and Inclusion in Code-Mixed Texts (Balouchzahi et al., LTEDI 2021)
- PDF:
- https://preview.aclanthology.org/add_missing_videos/2021.ltedi-1.27.pdf
- Data
- Dakshina