Research map / Architectures and efficiency / RNNs and normalization
Syntactic Skeleton-Based Translation
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| add syntactic skeleton with partially syntactic rules to hierarchical phrase-based | Hierarchical Phrase-based · zh-en nw, zh-en web, en-zh tests | BLEU: +0.95 average (binary trees) | Helped |
| use binary parse trees instead of CTB-style trees for SYNSKEL (ablation) | SYNSKEL · zh-en nw, zh-en web, en-zh tests | BLEU: +0.71 -> +0.95 | Helped |
| use tree-parsing instead of string-parsing (ablation) | SYNSKEL · zh-en nw, zh-en web, en-zh tests | BLEU: +0.95 -> +0.91 | No clear effect |
| use binary forest instead of single binary tree (ablation) | SYNSKEL · zh-en nw, zh-en web, en-zh tests | BLEU: +0.91 -> +0.94 | No clear effect |
| SYNSKEL instead of Hier. + SAMT rules | SYNSKEL · zh-en nw, zh-en web, en-zh tests | BLEU: +0.35 -> +0.95 | Helped |
| limit maximum skeleton depth to 5 or less instead of unlimited (ablation) | SYNSKEL · zh-en newswire tuning | BLEU and decoding time | Mixed |
| use tree-to-string model alone instead of hierarchical phrase-based | Tree-to-String · zh-en nw, zh-en web, en-zh tests | BLEU: -0.77 (CTB), -0.39 (binary) | Hurt |
| add source syntax features to hierarchical phrase-based | Hierarchical Phrase-based · zh-en nw, zh-en web, en-zh tests | BLEU: +0.23 (CTB), +0.29 (binary) | Helped |
Closest papers by meaning
- Unsupervised Machine Translation Using Monolingual Corpora Only (ICLR 2018 · similarity 0.83)
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