Xuchen Yao


2015

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Lean Question Answering over Freebase from Scratch
Xuchen Yao
Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations

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Domain-Specific Paraphrase Extraction
Ellie Pavlick | Juri Ganitkevitch | Tsz Ping Chan | Xuchen Yao | Benjamin Van Durme | Chris Callison-Burch
Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)

2014

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Information Extraction over Structured Data: Question Answering with Freebase
Xuchen Yao | Benjamin Van Durme
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

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Freebase QA: Information Extraction or Semantic Parsing?
Xuchen Yao | Jonathan Berant | Benjamin Van Durme
Proceedings of the ACL 2014 Workshop on Semantic Parsing

2013

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Finding More Bilingual Webpages with High Credibility via Link Analysis
Chengzhi Zhang | Xuchen Yao | Chunyu Kit
Proceedings of the Sixth Workshop on Building and Using Comparable Corpora

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Answer Extraction as Sequence Tagging with Tree Edit Distance
Xuchen Yao | Benjamin Van Durme | Chris Callison-Burch | Peter Clark
Proceedings of the 2013 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

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Semi-Markov Phrase-Based Monolingual Alignment
Xuchen Yao | Benjamin Van Durme | Chris Callison-Burch | Peter Clark
Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing

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PARMA: A Predicate Argument Aligner
Travis Wolfe | Benjamin Van Durme | Mark Dredze | Nicholas Andrews | Charley Beller | Chris Callison-Burch | Jay DeYoung | Justin Snyder | Jonathan Weese | Tan Xu | Xuchen Yao
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

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Automatic Coupling of Answer Extraction and Information Retrieval
Xuchen Yao | Benjamin Van Durme | Peter Clark
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

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A Lightweight and High Performance Monolingual Word Aligner
Xuchen Yao | Benjamin Van Durme | Chris Callison-Burch | Peter Clark
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

2012

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Expectations of Word Sense in Parallel Corpora
Xuchen Yao | Benjamin Van Durme | Chris Callison-Burch
Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

2011

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Nonparametric Bayesian Word Sense Induction
Xuchen Yao | Benjamin Van Durme
Proceedings of TextGraphs-6: Graph-based Methods for Natural Language Processing

2010

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PDTB XML: the XMLization of the Penn Discourse TreeBank 2.0
Xuchen Yao | Irina Borisova | Mehwish Alam
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

The current study presents a conversion and unification of the Penn Discourse TreeBank 2.0 (PDTB) and the Penn TreeBank (PTB) under XML format. The main goal of the PDTB XML is to create a tool for efficient and broad querying of the syntax and discourse information simultaneously. The key stages of the project are developing proper cross-references between different data types and their representation in the modified TIGER-XML format, and then writing the required declarative languages (XML Schema). PTB XML is compatible with TIGER-XML format. The PDTB XML is developed as a unified format for the convenience of XQuery users; it integrates discourse relations and XML structures into one unified hierarchy and builds the cross references between the syntactic trees and the discourse relations. The syntactic and discourse elements are assigned with unique IDs in order to build cross-references between them. The converted corpus allows for a simultaneous search for syntactically specified discourse information based on the XQuery standard, which is illustrated with a simple example in the article.

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Practical Evaluation of Speech Recognizers for Virtual Human Dialogue Systems
Xuchen Yao | Pravin Bhutada | Kallirroi Georgila | Kenji Sagae | Ron Artstein | David Traum
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

We perform a large-scale evaluation of multiple off-the-shelf speech recognizers across diverse domains for virtual human dialogue systems. Our evaluation is aimed at speech recognition consumers and potential consumers with limited experience with readily available recognizers. We focus on practical factors to determine what levels of performance can be expected from different available recognizers in various projects featuring different types of conversational utterances. Our results show that there is no single recognizer that outperforms all other recognizers in all domains. The performance of each recognizer may vary significantly depending on the domain, the size and perplexity of the corpus, the out-of-vocabulary rate, and whether acoustic and language model adaptation has been used or not. We expect that our evaluation will prove useful to other speech recognition consumers, especially in the dialogue community, and will shed some light on the key problem in spoken dialogue systems of selecting the most suitable available speech recognition system for a particular application, and what impact training will have.