Papers Parallel Corpus Mining
“Parallel Corpus Mining” 태그가 달린 논문 13편 · 필터 해제
Bilingual Corpus Mining and Multistage Fine-Tuning for Improving Machine Translation of Lecture Transcripts
Lecture transcript translation helps learners understand online courses, however, building a high-quality lecture machine translation system lacks publicly available parallel corpora. To address this, we examine a framew…
BenchmarkingMachine TranslationParallel Corpus MiningSentence+1Better Quality Estimation for Low Resource Corpus Mining
Quality Estimation (QE) models have the potential to change how we evaluate and maybe even train machine translation models. However, these models still lack the robustness to achieve general adoption. We show that State…
Contrastive LearningData AugmentationMachine TranslationParallel Corpus Mining+1USCORE: An Effective Approach to Fully Unsupervised Evaluation Metrics for Machine Translation
The vast majority of evaluation metrics for machine translation are supervised, i.e., (i) are trained on human scores, (ii) assume the existence of reference translations, or (iii) leverage parallel data. This hinders th…
Machine TranslationParallel Corpus MiningSentenceSentence Embeddings+1Unsupervised Multilingual Sentence Embeddings for Parallel Corpus Mining
Existing models of multilingual sentence embeddings require large parallel data resources which are not available for low-resource languages. We propose a novel unsupervised method to derive multilingual sentence embeddi…
Language ModelingLanguage ModellingMachine TranslationParallel Corpus Mining+4Unsupervised Parallel Corpus Mining on Web Data
With a large amount of parallel data, neural machine translation systems are able to deliver human-level performance for sentence-level translation. However, it is costly to label a large amount of parallel data by human…
Machine TranslationParallel Corpus MiningSentenceTranslationParallel Sentence Mining by Constrained Decoding
We present a novel method to extract parallel sentences from two monolingual corpora, using neural machine translation. Our method relies on translating sentences in one corpus, but constraining the decoding by a prefix …
Cross-Lingual Bitext MiningMachine TranslationParallel Corpus MiningSentence+1ParaCrawl: Web-Scale Acquisition of Parallel Corpora
We report on methods to create the largest publicly available parallel corpora by crawling the web, using open source software. We empirically compare alternative methods and publish benchmark data sets for sentence alig…
Machine TranslationParallel Corpus MiningSentenceTranslationMUSS: Multilingual Unsupervised Sentence Simplification by Mining Paraphrases
Progress in sentence simplification has been hindered by a lack of labeled parallel simplification data, particularly in languages other than English. We introduce MUSS, a Multilingual Unsupervised Sentence Simplificatio…
Parallel Corpus MiningSentenceText SimplificationCoursera Corpus Mining and Multistage Fine-Tuning for Improving Lectures Translation
Lectures translation is a case of spoken language translation and there is a lack of publicly available parallel corpora for this purpose. To address this, we examine a language independent framework for parallel corpus …
BenchmarkingDomain AdaptationMachine TranslationParallel Corpus Mining+2Hierarchical Document Encoder for Parallel Corpus Mining
We explore using multilingual document embeddings for nearest neighbor mining of parallel data. Three document-level representations are investigated: (i) document embeddings generated by simply averaging multilingual se…
Parallel Corpus MiningSentenceSentence EmbeddingSentence-Embedding+1Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyond
We introduce an architecture to learn joint multilingual sentence representations for 93 languages, belonging to more than 30 different families and written in 28 different scripts. Our system uses a single BiLSTM encode…
Cross-Lingual Bitext MiningCross-Lingual Document ClassificationCross-Lingual Natural Language InferenceCross-Lingual Transfer+8Margin-based Parallel Corpus Mining with Multilingual Sentence Embeddings
Machine translation is highly sensitive to the size and quality of the training data, which has led to an increasing interest in collecting and filtering large parallel corpora. In this paper, we propose a new method for…
Cross-Lingual Bitext MiningMachine TranslationParallel Corpus MiningRetrieval+3Effective Parallel Corpus Mining using Bilingual Sentence Embeddings
This paper presents an effective approach for parallel corpus mining using bilingual sentence embeddings. Our embedding models are trained to produce similar representations exclusively for bilingual sentence pairs that …
Machine TranslationNMTParallel Corpus MiningSemantic Similarity+4