tailieunhanh - Báo cáo khoa học: "Statistical Machine Translation with Word- and Sentence-Aligned Parallel Corpora"

The parameters of statistical translation models are typically estimated from sentence-aligned parallel corpora. We show that significant improvements in the alignment and translation quality of such models can be achieved by additionally including wordaligned data during training. Incorporating wordlevel alignments into the parameter estimation of the IBM models reduces alignment error rate and increases the Bleu score when compared to training the same models only on sentence-aligned data. . | Statistical Machine Translation with Word- and Sentence-Aligned Parallel Corpora Chris Callison-Burch David Talbot Miles Osborne School on Informatics University of Edinburgh 2 Buccleuch Place Edinburgh EH8 9LW callison-burch@ Abstract The parameters of statistical translation models are typically estimated from sentence-aligned parallel corpora. We show that significant improvements in the alignment and translation quality of such models can be achieved by additionally including word-aligned data during training. Incorporating wordlevel alignments into the parameter estimation of the IBM models reduces alignment error rate and increases the Bleu score when compared to training the same models only on sentence-aligned data. On the Verbmobil data set we attain a 38 reduction in the alignment error rate and a higher Bleu score with half as many training examples. We discuss how varying the ratio of word-aligned to sentence-aligned data affects the expected performance gain. 1 Introduction Machine translation systems based on probabilistic translation models Brown et al. 1993 are generally trained using sentence-aligned parallel corpora. For many language pairs these exist in abundant quantities. However for new domains or uncommon language pairs extensive parallel corpora are often hard to come by. Two factors could increase the performance of statistical machine translation for new language pairs and domains a reduction in the cost of creating new training data and the development of more efficient methods for exploiting existing training data. Approaches such as harvesting parallel corpora from the web Resnik and Smith 2003 address the creation of data. We take the second complementary approach. We address the problem of efficiently exploiting existing parallel corpora by adding explicit word-level alignments between a number of the sentence pairs in the training corpus. We modify the standard parameter estimation procedure for IBM Models and HMM variants .

• Báo cáo khoa học
• Statistical Machine Translation
• Word and Sentence Aligned Parallel Corpora
• Chris Callison Burch David Talbot Miles Osborne
• báo cáo khoa học
• mô hình ngôn ngữ
• xử lý ngôn ngữ tự nhiên
• N gram based Statistical
• Machine Translation versus Syntax Augmented Machine Translation
• comparison and system combination
• scientific reports
• model language
• process natural language
• A Discriminative Latent Variable Model
• A Discriminative Latent Variable Model for Statistical Machine Translation
• báo cáo ngôn ngữ
• Mixing Multiple Translation Models
• SMT
• ngôn ngữ tự nhiên
• Translation Model Size Reduction
• Hierarchical Phrase based
• Translation Model Adaptation
• Monolingual Topic Information
• Name Translation
• Learning When to Transliterate
• Perplexity Minimization
• Translation Model Domain Adaptation
• Improving Pronoun Translation
• Liane Guillou
• Machine translation
• Domain adaptation
• The English Vietnamese language pair
• Low resource domains
• Khoa học máy tính
• Tạp chí khoa học
• Natural Language Processing
• Phrase based Statistical Machine Translation
• An Open Source Toolkit
• Tree Forest Based Statistical Machine Translation
• Xianchao Wu
• A Ranking based Approach
• Word Reordering
• Nan Yang†
• Mu Li
• Private Access
• Phrase Tables
• Fast and Scalable Decoding
• Language Model Look Ahead
• A Comparative Study
• Target Dependency Structures
• Enhancing Statistical Machine Translation
• Character Alignment
• Ning Xi
• Post ordering by Parsing
• Japanese English Statistical Machine Translation
• Isao Goto Masao Utiyama
• Modified Distortion Matrices
• Arianna Bisazza and Marcello Federico
• Syntax to Morphology Mapping in Factored
• Phrase Based Statistical Machine Translation from English to Turkish
• Reyyan Yeniterzi
• Error Detection
• Linguistic Features
• Improving Statistical Machine Translation
• Monolingual Collocation
• Zhanyi Liu
• Bilingual Sense Similarity
• Boxing Chen
• George Foster and Roland Kuhn
• Bucking the Trend
• Large Scale Cost Focused Active Learning
• Paraphrase Lattice
• Takashi Onishi and Masao Utiyama
• Filtering Syntactic Constraints
• Hailong Cao and Eiichiro Sumita