Using TERp to Augment the System Combination for SMT
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Summary
A TERp-based augmented system combination in terms of the backbone selection and consensus decoding network and a two-pass decoding strategy for the lattice-based phrase-level confusion network (CN) to generate the final result.
- Type
- article
- Published
- 2010-01-01
- Cited by
- 11
- References
- 28
- Access
- Open access
- OpenAlex
- https://openalex.org/W43079696
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:2875632
Keywords
Phrase, Computer science, Decoding methods, Metric (unit), Artificial intelligence
References
- Computing Consensus Translation for Multiple Machine Translation Systems Using Enhanced Hypothesis Alignment
- Computing consensus translation from multiple machine translation systems
- Disambiguating “DE” for Chinese-English Machine Translation
- Fluency, Adequacy, or HTER? Exploring Different Human Judgments with a Tunable MT Metric
- Incremental Hypothesis Alignment with Flexible Matching for Building Confusion Networks: BBN System Description for WMT09 System Combination Task
- Improving Alignments for Better Confusion Networks for Combining Machine Translation Systems
- Bleu: a Method for Automatic Evaluation of Machine Translation
- An Empirical Study on Computing Consensus Translations from Multiple Machine Translation Systems
- Re-evaluating Machine Translation Results with Paraphrase Support
- Incremental Hypothesis Alignment for Building Confusion Networks with Application to Machine Translation System Combination
- Consensus Network Decoding for Statistical Machine Translation System Combination
- Improved Word-Level System Combination for Machine Translation
- METEOR: An Automatic Metric for MT Evaluation with Improved Correlation with Human Judgments
- Moses: Open Source Toolkit for Statistical Machine Translation
- Lattice-based System Combination for Statistical Machine Translation
- Paraphrasing for Automatic Evaluation
- Minimum Bayes-Risk Decoding for Statistical Machine Translation
- Minimum Error Rate Training in Statistical Machine Translation
- A STUDY OF TRANSLATION ERROR RATE WITH TARGETED HUMAN ANNOTATION
- A Hierarchical Phrase-Based Model for Statistical Machine Translation
Cited by
- Topic Modeling-based Domain Adaptation for System Combination
- Phrase-level System Combination for Machine Translation Based on Target-to-Target Decoding
- Joint Space Neural Probabilistic Language Model for Statistical Machine Translation
- Neural Probabilistic Language Model for System Combination
- Hybrid System Combination for Machine Translation: An Integration of Phrase-level and Sentences-level Combination Approaches
- System Combination with Extra Alignment Information
- System Combination for Machine Translation through Paraphrasing
- Generating E-Commerce Product Titles and Predicting their Quality
- A Generative-Discriminative Framework for Title Generation in the E-commerce Domain
- Modeling Voting for System Combination in Machine Translation
- Sentence-Level Paraphrasing for Machine Translation System Combination
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