High Frequent In-domain Words Segmentation and Forward Translation for the WMT21 Biomedical Task
This paper reports the optimization of using the out-of-domain data in the Biomedical translation task. We firstly optimized our parallel training dataset using the BabelNet in-domain terminology words. Afterward, to increase the training set, we studied the effects of the out-of-domain data on biomedical translation tasks, and we created a mixture of in-domain and out-of-domain training sets and added more in-domain data using forward translation in the English-Spanish task. Finally, with a simple bpe optimization method, we increased the number of in-domain sub-words in our mixed training set and trained the Transformer model on the generated data. Results show improvements using our proposed method.
Code (0)
등록된 구현이 없습니다.
Tasks
TranslationSimilar Papers 제목 키워드 기반
Inducing Embeddings for Rare and Unseen Words by Leveraging Lexical Resources
We put forward an approach that exploits the knowledge encoded in lexical resources in order to induce representations for words that were not encountered frequently during training. Our approach provides an advantage ov…
Word EmbeddingsMulti-task Pairwise Neural Ranking for Hashtag Segmentation
Hashtags are often employed on social media and beyond to add metadata to a textual utterance with the goal of increasing discoverability, aiding search, or providing additional semantics. However, the semantic content o…
SegmentationSentiment AnalysisOnto Word Segmentation of the Complete Tang Poems
We aim at segmenting words in the Complete Tang Poems (CTP). Although it is possible to do some research about CTP without doing full-scale word segmentation, we must move forward to word-level analysis of CTP for conduc…
Source-Relaxed Domain Adaptation for Image Segmentation
Domain adaptation (DA) has drawn high interests for its capacity to adapt a model trained on labeled source data to perform well on unlabeled or weakly labeled target data from a different domain. Most common DA techniqu…
Domain AdaptationImage SegmentationSegmentationSemantic SegmentationBPE-Dropout: Simple and Effective Subword Regularization
Subword segmentation is widely used to address the open vocabulary problem in machine translation. The dominant approach to subword segmentation is Byte Pair Encoding (BPE), which keeps the most frequent words intact whi…
Machine TranslationSegmentationTranslation