Abstract
This report describes the Minimum Bayes Risk Quality Estimation (MBR-QE) submission to the Workshop on Machine Translation's 2023 Metrics Shared Task. MBR decoding with neural utility metrics like BLEURT is known to be effective in generating high quality machine translations. We use the underlying technique of MBR decoding and develop an MBR based reference-free (quality estimation) metric. Our method uses an evaluator machine translation system and a reference-based utility metric (specifically BLEURT and MetricX) to calculate a quality estimation score of a model's output. We report results related to comparing different MBR configurations and utility metrics.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 8th Conference on Machine Translation, WMT 2023 |
| Publisher | Association for Computational Linguistics |
| Pages | 804-809 |
| Number of pages | 6 |
| ISBN (Electronic) | 9798891760417 |
| State | Published - 2023 |
| Externally published | Yes |
| Event | 8th Conference on Machine Translation, WMT 2023 - Singapore, Singapore Duration: 6 Dec 2023 → 7 Dec 2023 |
Publication series
| Name | Conference on Machine Translation - Proceedings |
|---|---|
| ISSN (Electronic) | 2768-0983 |
Conference
| Conference | 8th Conference on Machine Translation, WMT 2023 |
|---|---|
| Country/Territory | Singapore |
| City | Singapore |
| Period | 6/12/23 → 7/12/23 |
Bibliographical note
Publisher Copyright:© 2023 Association for Computational Linguistics.
ASJC Scopus subject areas
- Language and Linguistics
- Human-Computer Interaction
- Software