Abstract
We present YiSi, a unified automatic semantic machine translation quality evaluation and estimation metric for languages with different levels of available resources. Underneath the interface with different language resources settings, YiSi uses the same representation for the two sentences in assessment. Besides, we show significant improvement in the correlation of YiSi-1’s scores with human judgment is made by using contextual embeddings in multilingual BERT–Bidirectional Encoder Representations from Transformers to evaluate lexical semantic similarity. YiSi is open source and publicly available.- Anthology ID:
- W19-5358
- Volume:
- Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1)
- Month:
- August
- Year:
- 2019
- Address:
- Florence, Italy
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 507–513
- Language:
- URL:
- https://aclanthology.org/W19-5358
- DOI:
- 10.18653/v1/W19-5358
- Cite (ACL):
- Chi-kiu Lo. 2019. YiSi - a Unified Semantic MT Quality Evaluation and Estimation Metric for Languages with Different Levels of Available Resources. In Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1), pages 507–513, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- YiSi - a Unified Semantic MT Quality Evaluation and Estimation Metric for Languages with Different Levels of Available Resources (Lo, WMT 2019)
- PDF:
- https://preview.aclanthology.org/starsem-semeval-split/W19-5358.pdf