Name
Title | ||
|---|---|---|
Metric Learning in Multilingual Sentence Similarity Measurement for Document Alignment. |
Abstract | ||
|---|---|---|
Document alignment techniques based on multilingual sentence representations have recently shown state of the art results. However, these techniques rely on unsupervised distance measurement techniques, which cannot be fined-tuned to the task at hand. In this paper, instead of these unsupervised distance measurement techniques, we employ Metric Learning to derive task-specific distance measurements. These measurements are supervised, meaning that the distance measurement metric is trained using a parallel dataset. Using a dataset belonging to English, Sinhala, and Tamil, which belong to three different language families, we show that these task-specific supervised distance learning metrics outperform their unsupervised counterparts, for document alignment. |
Year | Venue | DocType |
|---|---|---|
2021 | RANLP | Conference |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Charith Rajitha | 1 | 0 | 0.34 |
| Lakmali Piyarathne | 2 | 0 | 0.34 |
| Dilan Sachintha | 3 | 0 | 0.34 |
| Surangika Ranathunga | 4 | 51 | 17.93 |