Name
Title | ||
|---|---|---|
Machine Translation With Pre-Specified Target-Side Words Using A Semi-Autoregressive Model |
Abstract | ||
|---|---|---|
We introduce our TMU Japanese-to-English system, which employs a semi-autoregressive model, to tackle the WAT 2021 (Nakazawa et al., 2021) restricted translation task. In this task, we translate an input sentence with the constraint that some words, called restricted target vocabularies (RTVs), must be contained in the output sentence. To satisfy this constraint, we use a semi-autoregressive model, namely, RecoverSAT (Ran et al., 2020), due to its ability (known as "forced translation") to insert specified words into the output sentence. When using "forced translation," the order of inserting RTVs is a critical problem. In our system, we obtain word alignment between a source sentence and the corresponding RTVs and then sort the RTVs in the order of their corresponding words or phrases in the source sentence. Using the model with sorted order RTVs, we succeeded in inserting all the RTVs into output sentences in more than 96% of the test sentences. Moreover, we confirmed that sorting RTVs improved the BLEU score compared with random order RTVs. |
Year | Venue | DocType |
|---|---|---|
2021 | WAT 2021: THE 8TH WORKSHOP ON ASIAN TRANSLATION | Conference |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Seiichiro Kondo | 1 | 1 | 1.09 |
| Aomi Koyama | 2 | 0 | 0.68 |
| Tomoshige Kiyuna | 3 | 0 | 0.34 |
| Tosho Hirasawa | 4 | 0 | 3.38 |
| Mamoru Komachi | 5 | 241 | 44.56 |