Word Embedding Evaluation for Sinhala
Dimuthu Lakmal, Surangika Ranathunga, Saman Peramuna, Indu Herath
Abstract
This paper presents the first ever comprehensive evaluation of different types of word embeddings for Sinhala language. Three standard word embedding models, namely, Word2Vec (both Skipgram and CBOW), FastText, and Glove are evaluated under two types of evaluation methods: intrinsic evaluation and extrinsic evaluation. Word analogy and word relatedness evaluations were performed in terms of intrinsic evaluation, while sentiment analysis and part-of-speech (POS) tagging were conducted as the extrinsic evaluation tasks. Benchmark datasets used for intrinsic evaluations were carefully crafted considering specific linguistic features of Sinhala. In general, FastText word embeddings with 300 dimensions reported the finest accuracies across all the evaluation tasks, while Glove reported the lowest results.- Anthology ID:
- 2020.lrec-1.231
- Volume:
- Proceedings of the Twelfth Language Resources and Evaluation Conference
- Month:
- May
- Year:
- 2020
- Address:
- Marseille, France
- Editors:
- Nicoletta Calzolari, Frédéric Béchet, Philippe Blache, Khalid Choukri, Christopher Cieri, Thierry Declerck, Sara Goggi, Hitoshi Isahara, Bente Maegaard, Joseph Mariani, Hélène Mazo, Asuncion Moreno, Jan Odijk, Stelios Piperidis
- Venue:
- LREC
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 1874–1881
- Language:
- English
- URL:
- https://aclanthology.org/2020.lrec-1.231
- DOI:
- Cite (ACL):
- Dimuthu Lakmal, Surangika Ranathunga, Saman Peramuna, and Indu Herath. 2020. Word Embedding Evaluation for Sinhala. In Proceedings of the Twelfth Language Resources and Evaluation Conference, pages 1874–1881, Marseille, France. European Language Resources Association.
- Cite (Informal):
- Word Embedding Evaluation for Sinhala (Lakmal et al., LREC 2020)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-2/2020.lrec-1.231.pdf