Word Alignment
84 papers with code • 7 benchmarks • 4 datasets
Word Alignment is the task of finding the correspondence between source and target words in a pair of sentences that are translations of each other.
Source: Neural Network-based Word Alignment through Score Aggregation
Benchmarks
These leaderboards are used to track progress in Word Alignment
| Trend | Dataset | Best Model | Paper | Code | Compare |
|---|---|---|---|---|---|
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
|||||
|
WMT 2016 News
MUSE
Europarl ConcoDisco Dataset
Bangla Word Analogy
Latest papers with no code
Learning Trajectory-Word Alignments for Video-Language Tasks
To amend this, we propose a novel TW-BERT to learn Trajectory-Word alignment by a newly designed trajectory-to-word (T2W) attention for solving video-language tasks.
Word Alignment in the Era of Deep Learning: A Tutorial
Jumping forward to the era of neural machine translation (NMT), we show how insights from word alignment inspired the attention mechanism fundamental to present-day NMT.
EntityCS: Improving Zero-Shot Cross-lingual Transfer with Entity-Centric Code Switching
We use Wikidata and English Wikipedia to construct an entity-centric CS corpus by switching entities to their counterparts in other languages.
Extending Word-Level Quality Estimation for Post-Editing Assistance
Based on extended word alignment, we further propose a novel task called refined word-level QE that outputs refined tags and word-level correspondences.
When do Contrastive Word Alignments Improve Many-to-many Neural Machine Translation?
Meanwhile, the contrastive objective can implicitly utilize automatically learned word alignment, which has not been explored in many-to-many NMT.
Graph Neural Networks for Multiparallel Word Alignment
First, we create a multiparallel word alignment graph, joining all bilingual word alignment pairs in one graph.
Embedding-Enhanced GIZA++: Improving Low-Resource Word Alignment Using Embeddings
In the lowest-resource setting, we outperform GIZA++ by 8. 5, 10. 9, and 12 AER for Ro-En, De-En, and En-Fr, respectively.
When do Contrastive Word Alignments Improve Many-to-many Neural Machine Translation?
Meanwhile, the contrastive objective can implicitly utilize automatically learned word alignment, which has not been explored in many-to-many NMT.
Multi-Stage Framework with Refinement based Point Set Registration for Unsupervised Bi-Lingual Word Alignment
Cross-lingual alignment of word embeddings play an important role in knowledge transfer across languages, for improving machine translation and other multi-lingual applications.
ATOGAN:Adaptive Training Objective Generative Adversarial Network for Cross-lingual Word Alignment in Non-Isomorphic Embedding Spaces
Cross-lingual word alignment is a task for word translation from monolingual word embedding spaces of two languages.
