TAILIEUCHUNG - Báo cáo khoa học: "Word Alignment and Cross-Lingual Resource Acquisition"

Annotated corpora are valuable resources for developing Natural Language Processing applications. This work focuses on acquiring annotated data for multilingual processing applications. We present an annotation environment that supports a web-based user-interface for acquiring word alignments between English and Chinese as well as a visualization tool for researchers to explore the annotated data. | Word Alignment and Cross-Lingual Resource Acquisition Carol Nichols and Rebecca Hwa Department of Computer Science University of Pittsburgh Pittsburgh PA 15260 cln23 hwa @ Abstract Annotated corpora are valuable resources for developing Natural Language Processing applications. This work focuses on acquiring annotated data for multilingual processing applications. We present an annotation environment that supports a web-based user-interface for acquiring word alignments between English and Chinese as well as a visualization tool for researchers to explore the annotated data. 1 Introduction The performance of many Natural Language Processing NLP applications can be improved through supervised machine learning techniques that train systems with annotated training examples. For example a part-of-speech POS tagger might be induced from words that have been annotated with the correct POS tags. A limitation to the supervised approach is that the annotation is typically performed manually. This poses as a challenge in three ways. First researchers must develop a comprehensive annotation guideline for the annotators to follow. Guideline development is difficult because researchers must be specific enough so that different annotators work will be comparable but also general enough to allow the annotators to make their own linguistic judgments. Reported experiences of previous annotation projects suggest that guideline development is both an art and a science and is itself This work has been supported in part by CRAW Distributed Mentor Program. We thank Karina Iva-netich David Chiang and the NLP group at Pitt for helpful feedbacks on the user interfaces Wanwan Zhang and Ying-Ju Suen for testing the system and the anonymous reviewers for their comments on the paper. a time-consuming process Litman and Pan 2002 Marcus et al. 1993 Xia et al. 2000 Wiebe 2002 . Second it is common for the annotators to make mistakes so some form of consistency check is necessary. Third

• Báo cáo khoa học
• Word Alignment
• Cross Lingual Resource Acquisition
• Carol Nichols and Rebecca Hwa
• báo cáo khoa học
• mô hình ngôn ngữ
• xử lý ngôn ngữ tự nhiên
• Smaller Alignment Models for Better Translations
• Unsupervised Word Alignment with the 0
• Ashish Vaswani Liang Huang David Chiang
• báo cáo ngôn ngữ
• ngôn ngữ tự nhiên
• Alignment Model Adaptation
• Domain Specific Word Alignment
• WU Hua
• Word Alignment Combination
• Multiple Word Segmentation
• Ning Xi
• Guangchao Tang
• Bootstrapping Word Alignment
• Word Packing
• Yanjun Ma
• Nicolas Stroppa
• Sentence alignment
• Parallel corpora
• word clustering
• Natural language processing
• Alignment algorithms
• IBM model
• Hierarchical Search
• Long Papers
• Diversify and Combine
• Improving Word Alignment
• Machine Translation
• Low Resource Languages
• Synonym Regularization
• Hiroyuki Shindo
• Supervised Word Alignment
• Jinxi Xu and Jinying Chen
• Active Learning Based Elicitation
• Semi Supervised Word Alignment
• Vamshi Ambati
• Submodular Maximization over Matroids
• Hui Lin
• Dealing with Spurious Ambiguity
• Learning ITG based Word Alignment
• Stephan Vogel
• Confidence Measure
• Fei Huang
• Unsupervised Word Alignment
• Arbitrary Features
• Chris Dyer Jonathan
• An Algorithm
• Unsupervised Transliteration Mining
• Application to Word Alignment
• Data Cleaning
• Tsuyoshi Okita
• Mining Parenthetical Translations
• Web by Word Alignment
• Dekang Lin
• Discriminative Word Alignment
• Conditional Random Fields
• Phil Blunsom and Trevor Cohn
• Improved Discriminative
• Bilingual Word Alignment
• Robert C
• Moore Wen tau Yih
• Word Alignment in English Hindi Parallel Corpus
• Recency Vector Approach
• Some Studies
• Soft Syntactic Constraints
• Discriminative Training
• Semi Supervised Training
• Statistical Word Alignment
• Alexander Fraser
• Yet Another Word Alignment Tool
• Ulrich Germann
• Optimizing Word Alignment Combination
• Phrase Table Training
• Yonggang Deng and Bowen Zhou
• Finding Synonyms
• Automatic Word Alignment
• Measures of Distributional Similarity