Dekai Wu


2020

pdf bib
Proceedings of the 17th International Conference on Spoken Language Translation
Marcello Federico | Alex Waibel | Kevin Knight | Satoshi Nakamura | Hermann Ney | Jan Niehues | Sebastian Stüker | Dekai Wu | Joseph Mariani | Francois Yvon
Proceedings of the 17th International Conference on Spoken Language Translation

2016

pdf bib
Learning Translations for Tagged Words: Extending the Translation Lexicon of an ITG for Low Resource Languages
Markus Saers | Dekai Wu
Proceedings of the Workshop on Multilingual and Cross-lingual Methods in NLP

pdf bib
Proceedings of the 6th Workshop on South and Southeast Asian Natural Language Processing (WSSANLP2016)
Dekai Wu | Pushpak Bhattacharyya
Proceedings of the 6th Workshop on South and Southeast Asian Natural Language Processing (WSSANLP2016)

pdf bib
Improving word alignment for low resource languages using English monolingual SRL
Meriem Beloucif | Markus Saers | Dekai Wu
Proceedings of the Sixth Workshop on Hybrid Approaches to Translation (HyTra6)

We introduce a new statistical machine translation approach specifically geared to learning translation from low resource languages, that exploits monolingual English semantic parsing to bias inversion transduction grammar (ITG) induction. We show that in contrast to conventional statistical machine translation (SMT) training methods, which rely heavily on phrase memorization, our approach focuses on learning bilingual correlations that help translating low resource languages, by using the output language semantic structure to further narrow down ITG constraints. This approach is motivated by previous research which has shown that injecting a semantic frame based objective function while training SMT models improves the translation quality. We show that including a monolingual semantic objective function during the learning of the translation model leads towards a semantically driven alignment which is more efficient than simply tuning loglinear mixture weights against a semantic frame based evaluation metric in the final stage of statistical machine translation training. We test our approach with three different language pairs and demonstrate that our model biases the learning towards more semantically correct alignments. Both GIZA++ and ITG based techniques fail to capture meaningful bilingual constituents, which is required when trying to learn translation models for low resource languages. In contrast, our proposed model not only improve translation by injecting a monolingual objective function to learn bilingual correlations during early training of the translation model, but also helps to learn more meaningful correlations with a relatively small data set, leading to a better alignment compared to either conventional ITG or traditional GIZA++ based approaches.

pdf bib
Driving inversion transduction grammar induction with semantic evaluation
Meriem Beloucif | Dekai Wu
Proceedings of the Fifth Joint Conference on Lexical and Computational Semantics

2015

pdf bib
Proceedings of the Ninth Workshop on Syntax, Semantics and Structure in Statistical Translation
Dekai Wu | Marine Carpuat | Eneko Agirre | Nora Aranberri
Proceedings of the Ninth Workshop on Syntax, Semantics and Structure in Statistical Translation

pdf bib
Improving evaluation and optimization of MT systems against MEANT
Chi-kiu Lo | Philipp Dowling | Dekai Wu
Proceedings of the Tenth Workshop on Statistical Machine Translation

2014

pdf bib
XMEANT: Better semantic MT evaluation without reference translations
Chi-kiu Lo | Meriem Beloucif | Markus Saers | Dekai Wu
Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

pdf bib
Proceedings of SSST-8, Eighth Workshop on Syntax, Semantics and Structure in Statistical Translation
Dekai Wu | Marine Carpuat | Xavier Carreras | Eva Maria Vecchi
Proceedings of SSST-8, Eighth Workshop on Syntax, Semantics and Structure in Statistical Translation

pdf bib
Better Semantic Frame Based MT Evaluation via Inversion Transduction Grammars
Dekai Wu | Chi-kiu Lo | Meriem Beloucif | Markus Saers
Proceedings of SSST-8, Eighth Workshop on Syntax, Semantics and Structure in Statistical Translation

pdf bib
Ternary Segmentation for Improving Search in Top-down Induction of Segmental ITGs
Markus Saers | Dekai Wu
Proceedings of SSST-8, Eighth Workshop on Syntax, Semantics and Structure in Statistical Translation

pdf bib
Transduction Recursive Auto-Associative Memory: Learning Bilingual Compositional Distributed Vector Representations of Inversion Transduction Grammars
Karteek Addanki | Dekai Wu
Proceedings of SSST-8, Eighth Workshop on Syntax, Semantics and Structure in Statistical Translation

pdf bib
Lexical Access Preference and Constraint Strategies for Improving Multiword Expression Association within Semantic MT Evaluation
Dekai Wu | Chi-kiu Lo | Markus Saers
Proceedings of the 4th Workshop on Cognitive Aspects of the Lexicon (CogALex)

pdf bib
Evaluating Improvised Hip Hop Lyrics - Challenges and Observations
Karteek Addanki | Dekai Wu
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

We investigate novel challenges involved in comparing model performance on the task of improvising responses to hip hop lyrics and discuss observations regarding inter-evaluator agreement on judging improvisation quality. We believe the analysis serves as a first step toward designing robust evaluation strategies for improvisation tasks, a relatively neglected area to date. Unlike most natural language processing tasks, improvisation tasks suffer from a high degree of subjectivity, making it difficult to design discriminative evaluation strategies to drive model development. We propose a simple strategy with fluency and rhyming as the criteria for evaluating the quality of generated responses, which we apply to both our inversion transduction grammar based FREESTYLE hip hop challenge-response improvisation system, as well as various contrastive systems. We report inter-evaluator agreement for both English and French hip hop lyrics, and analyze correlation with challenge length. We also compare the extent of agreement in evaluating fluency with that of rhyming, and quantify the difference in agreement with and without precise definitions of evaluation criteria.

pdf bib
On the reliability and inter-annotator agreement of human semantic MT evaluation via HMEANT
Chi-kiu Lo | Dekai Wu
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

We present analyses showing that HMEANT is a reliable, accurate and fine-grained semantic frame based human MT evaluation metric with high inter-annotator agreement (IAA) and correlation with human adequacy judgments, despite only requiring a minimal training of about 15 minutes for lay annotators. Previous work shows that the IAA on the semantic role labeling (SRL) subtask within HMEANT is over 70%. In this paper we focus on (1) the IAA on the semantic role alignment task and (2) the overall IAA of HMEANT. Our results show that the IAA on the alignment task of HMEANT is over 90% when humans align SRL output from the same SRL annotator, which shows that the instructions on the alignment task are sufficiently precise, although the overall IAA where humans align SRL output from different SRL annotators falls to only 61% due to the pipeline effect on the disagreement in the two annotation task. We show that instead of manually aligning the semantic roles using an automatic algorithm not only helps maintaining the overall IAA of HMEANT at 70%, but also provides a finer-grained assessment on the phrasal similarity of the semantic role fillers. This suggests that HMEANT equipped with automatic alignment is reliable and accurate for humans to evaluate MT adequacy while achieving higher correlation with human adequacy judgments than HTER.

2013

pdf bib
Learning to Freestyle: Hip Hop Challenge-Response Induction via Transduction Rule Segmentation
Dekai Wu | Karteek Addanki | Markus Saers | Meriem Beloucif
Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing

pdf bib
Bayesian Induction of Bracketing Inversion Transduction Grammars
Markus Saers | Dekai Wu
Proceedings of the Sixth International Joint Conference on Natural Language Processing

pdf bib
Proceedings of the Seventh Workshop on Syntax, Semantics and Structure in Statistical Translation
Marine Carpuat | Lucia Specia | Dekai Wu
Proceedings of the Seventh Workshop on Syntax, Semantics and Structure in Statistical Translation

pdf bib
Combining Top-down and Bottom-up Search for Unsupervised Induction of Transduction Grammars
Markus Saers | Karteek Addanki | Dekai Wu
Proceedings of the Seventh Workshop on Syntax, Semantics and Structure in Statistical Translation

pdf bib
MEANT at WMT 2013: A Tunable, Accurate yet Inexpensive Semantic Frame Based MT Evaluation Metric
Chi-kiu Lo | Dekai Wu
Proceedings of the Eighth Workshop on Statistical Machine Translation

pdf bib
Unsupervised Transduction Grammar Induction via Minimum Description Length
Markus Saers | Karteek Addanki | Dekai Wu
Proceedings of the Second Workshop on Hybrid Approaches to Translation

pdf bib
Unsupervised Learning of Bilingual Categories in Inversion Transduction Grammar Induction
Markus Saers | Dekai Wu
Proceedings of the 13th International Conference on Parsing Technologies (IWPT 2013)

pdf bib
Improving machine translation by training against an automatic semantic frame based evaluation metric
Chi-kiu Lo | Karteek Addanki | Markus Saers | Dekai Wu
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

pdf bib
Segmenting vs. Chunking Rules: Unsupervised ITG Induction via Minimum Conditional Description Length
Markus Saers | Karteek Addanki | Dekai Wu
Proceedings of the International Conference Recent Advances in Natural Language Processing RANLP 2013

2012

pdf bib
LTG vs. ITG Coverage of Cross-Lingual Verb Frame Alternations
Karteek Addanki | Chi-kiu Lo | Markus Saers | Dekai Wu
Proceedings of the 16th Annual conference of the European Association for Machine Translation

pdf bib
Fully Automatic Semantic MT Evaluation
Chi-kiu Lo | Anand Karthik Tumuluru | Dekai Wu
Proceedings of the Seventh Workshop on Statistical Machine Translation

pdf bib
Proceedings of the Sixth Workshop on Syntax, Semantics and Structure in Statistical Translation
Marine Carpuat | Lucia Specia | Dekai Wu
Proceedings of the Sixth Workshop on Syntax, Semantics and Structure in Statistical Translation

pdf bib
Towards a Predicate-Argument Evaluation for MT
Ondřej Bojar | Dekai Wu
Proceedings of the Sixth Workshop on Syntax, Semantics and Structure in Statistical Translation

pdf bib
Unsupervised vs. supervised weight estimation for semantic MT evaluation metrics
Chi-kiu Lo | Dekai Wu
Proceedings of the Sixth Workshop on Syntax, Semantics and Structure in Statistical Translation

pdf bib
Accuracy and robustness in measuring the lexical similarity of semantic role fillers for automatic semantic MT evaluation
Anand Karthik Tumuluru | Chi-kiu Lo | Dekai Wu
Proceedings of the 26th Pacific Asia Conference on Language, Information, and Computation

pdf bib
From Finite-State to Inversion Transductions: Toward Unsupervised Bilingual Grammar Induction
Markus Saers | Karteek Addanki | Dekai Wu
Proceedings of COLING 2012

2011

pdf bib
Linear Transduction Grammars and Zipper Finite-State Transducers
Markus Saers | Dekai Wu
Proceedings of the International Conference Recent Advances in Natural Language Processing 2011

pdf bib
Proceedings of Fifth Workshop on Syntax, Semantics and Structure in Statistical Translation
Dekai Wu | Marianna Apidianaki | Marine Carpuat | Lucia Specia
Proceedings of Fifth Workshop on Syntax, Semantics and Structure in Statistical Translation

pdf bib
Structured vs. Flat Semantic Role Representations for Machine Translation Evaluation
Chi-kiu Lo | Dekai Wu
Proceedings of Fifth Workshop on Syntax, Semantics and Structure in Statistical Translation

pdf bib
Reestimation of Reified Rules in Semiring Parsing and Biparsing
Markus Saers | Dekai Wu
Proceedings of Fifth Workshop on Syntax, Semantics and Structure in Statistical Translation

pdf bib
Mining Parallel Documents Using Low Bandwidth and High Precision CLIR from the Heterogeneous Web
Simon Shi | Pascale Fung | Emmanuel Prochasson | Chi-kiu Lo | Dekai Wu
Proceedings of 5th International Joint Conference on Natural Language Processing

pdf bib
Principled Induction of Phrasal Bilexica
Markus Saers | Dekai Wu
Proceedings of the 15th Annual conference of the European Association for Machine Translation

pdf bib
MEANT: An inexpensive, high-accuracy, semi-automatic metric for evaluating translation utility based on semantic roles
Chi-kiu Lo | Dekai Wu
Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies

2010

pdf bib
Word Alignment with Stochastic Bracketing Linear Inversion Transduction Grammar
Markus Saers | Joakim Nivre | Dekai Wu
Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics

pdf bib
Linear Inversion Transduction Grammar Alignments as a Second Translation Path
Markus Saers | Joakim Nivre | Dekai Wu
Proceedings of the Joint Fifth Workshop on Statistical Machine Translation and MetricsMATR

pdf bib
Proceedings of the 4th Workshop on Syntax and Structure in Statistical Translation
Dekai Wu
Proceedings of the 4th Workshop on Syntax and Structure in Statistical Translation

pdf bib
A Systematic Comparison between Inversion Transduction Grammar and Linear Transduction Grammar for Word Alignment
Markus Saers | Joakim Nivre | Dekai Wu
Proceedings of the 4th Workshop on Syntax and Structure in Statistical Translation

pdf bib
Semantic vs. Syntactic vs. N-gram Structure for Machine Translation Evaluation
Chi-kiu Lo | Dekai Wu
Proceedings of the 4th Workshop on Syntax and Structure in Statistical Translation

pdf bib
Evaluating Machine Translation Utility via Semantic Role Labels
Chi-kiu Lo | Dekai Wu
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

We present the methodology that underlies mew metrics for semantic machine translation evaluation we are developing. Unlike widely-used lexical and n-gram based MT evaluation metrics, the aim of semantic MT evaluation is to measure the utility of translations. We discuss the design of empirical studies to evaluate the utility of machine translation output by assessing the accuracy for key semantic roles. These roles are from the English 5W templates (who, what, when, where, why) used in recent GALE distillation evaluations. Recent work by Wu and Fung (2009) introduced semantic role labeling into statistical machine translation to enhance the quality of MT output. However, this approach has so far only been evaluated using lexical and n-gram based SMT evaluation metrics like BLEU which are not aimed at evaluating the utility of MT output. Direct data analysis are still needed to understand how semantic models can be leveraged to evaluate the utility of MT output. In this paper, we discuss a new methodology for evaluating the utility of the machine translation output, by assessing the accuracy with which human readers are able to complete the English 5W templates.

2009

pdf bib
Proceedings of the Third Workshop on Syntax and Structure in Statistical Translation (SSST-3) at NAACL HLT 2009
Dekai Wu | David Chiang
Proceedings of the Third Workshop on Syntax and Structure in Statistical Translation (SSST-3) at NAACL HLT 2009

pdf bib
Improving Phrase-Based Translation via Word Alignments from Stochastic Inversion Transduction Grammars
Markus Saers | Dekai Wu
Proceedings of the Third Workshop on Syntax and Structure in Statistical Translation (SSST-3) at NAACL HLT 2009

pdf bib
Learning Stochastic Bracketing Inversion Transduction Grammars with a Cubic Time Biparsing Algorithm
Markus Saers | Joakim Nivre | Dekai Wu
Proceedings of the 11th International Conference on Parsing Technologies (IWPT’09)

pdf bib
Empirical lower bounds on translation unit error rate for the full class of inversion transduction grammars
Anders Søgaard | Dekai Wu
Proceedings of the 11th International Conference on Parsing Technologies (IWPT’09)

pdf bib
Can Semantic Role Labeling Improve SMT?
Dekai Wu | Pascale Fung
Proceedings of the 13th Annual conference of the European Association for Machine Translation

pdf bib
Semantic Roles for SMT: A Hybrid Two-Pass Model
Dekai Wu | Pascale Fung
Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers

2008

pdf bib
Evaluation of Context-Dependent Phrasal Translation Lexicons for Statistical Machine Translation
Marine Carpuat | Dekai Wu
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)

We present new direct data analysis showing that dynamically-built context-dependent phrasal translation lexicons are more useful resources for phrase-based statistical machine translation (SMT) than conventional static phrasal translation lexicons, which ignore all contextual information. After several years of surprising negative results, recent work suggests that context-dependent phrasal translation lexicons are an appropriate framework to successfully incorporate Word Sense Disambiguation (WSD) modeling into SMT. However, this approach has so far only been evaluated using automatic translation quality metrics, which are important, but aggregate many different factors. A direct analysis is still needed to understand how context-dependent phrasal translation lexicons impact translation quality, and whether the additional complexity they introduce is really necessary. In this paper, we focus on the impact of context-dependent translation lexicons on lexical choice in phrase-based SMT and show that context-dependent lexicons are more useful to a phrase-based SMT system than a conventional lexicon. A typical phrase-based SMT system makes use of more and longer phrases with context modeling, including phrases that were not seen very frequently in training. Even when the segmentation is identical, the context-dependent lexicons yield translations that match references more often than conventional lexicons.

pdf bib
Proceedings of the ACL-08: HLT Second Workshop on Syntax and Structure in Statistical Translation (SSST-2)
David Chiang | Dekai Wu
Proceedings of the ACL-08: HLT Second Workshop on Syntax and Structure in Statistical Translation (SSST-2)

2007

pdf bib
Proceedings of SSST, NAACL-HLT 2007 / AMTA Workshop on Syntax and Structure in Statistical Translation
Dekai Wu | David Chiang
Proceedings of SSST, NAACL-HLT 2007 / AMTA Workshop on Syntax and Structure in Statistical Translation

pdf bib
Improving Statistical Machine Translation Using Word Sense Disambiguation
Marine Carpuat | Dekai Wu
Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning (EMNLP-CoNLL)

2006

pdf bib
A Grammatical Approach to Understanding Textual Tables Using Two-Dimensional SCFGs
Dekai Wu | Ken Wing Kuen Lee
Proceedings of the COLING/ACL 2006 Main Conference Poster Sessions

pdf bib
Boosting for Chinese Named Entity Recognition
Xiaofeng Yu | Marine Carpuat | Dekai Wu
Proceedings of the Fifth SIGHAN Workshop on Chinese Language Processing

2005

pdf bib
Inversion Transduction Grammar Constraints for Mining Parallel Sentences from Quasi-Comparable Corpora
Dekai Wu | Pascale Fung
Second International Joint Conference on Natural Language Processing: Full Papers

pdf bib
Evaluating the Word Sense Disambiguation Performance of Statistical Machine Translation
Marine Carpuat | Dekai Wu
Companion Volume to the Proceedings of Conference including Posters/Demos and tutorial abstracts

pdf bib
Statistical Machine Translation Part II: Tree-Based SMT
Dekai Wu
Companion Volume to the Proceedings of Conference including Posters/Demos and tutorial abstracts

pdf bib
Word Sense Disambiguation vs. Statistical Machine Translation
Marine Carpuat | Dekai Wu
Proceedings of the 43rd Annual Meeting of the Association for Computational Linguistics (ACL’05)

pdf bib
Recognizing Paraphrases and Textual Entailment Using Inversion Transduction Grammars
Dekai Wu
Proceedings of the ACL Workshop on Empirical Modeling of Semantic Equivalence and Entailment

2004

pdf bib
A Kernel PCA Method for Superior Word Sense Disambiguation
Dekai Wu | Weifeng Su | Marine Carpuat
Proceedings of the 42nd Annual Meeting of the Association for Computational Linguistics (ACL-04)

pdf bib
Why Nitpicking Works: Evidence for Occam’s Razor in Error Correctors
Dekai Wu | Grace Ngai | Marine Carpuat
COLING 2004: Proceedings of the 20th International Conference on Computational Linguistics

pdf bib
Semi-supervised training of a Kernel PCA-Based Model for Word Sense Disambiguation
Weifeng Su | Marine Carpuat | Dekai Wu
COLING 2004: Proceedings of the 20th International Conference on Computational Linguistics

pdf bib
Raising the Bar: Stacked Conservative Error Correction Beyond Boosting
Dekai Wu | Grace Ngai | Marine Carpuat
Proceedings of the Fourth International Conference on Language Resources and Evaluation (LREC’04)

pdf bib
Using N-best lists for Named Entity Recognition from Chinese Speech
Lufeng Zhai | Pascale Fung | Richard Schwartz | Marine Carpuat | Dekai Wu
Proceedings of HLT-NAACL 2004: Short Papers

pdf bib
An Efficient Algorithm to Induce Minimum Average Lookahead Grammars for Incremental LR Parsing
Dekai Wu | Yihai Shen
Proceedings of the Workshop on Incremental Parsing: Bringing Engineering and Cognition Together

pdf bib
Augmenting ensemble classification for Word Sense Disambiguation with a kernel PCA model
Marine Carpuat | Weifeng Su | Dekai Wu
Proceedings of SENSEVAL-3, the Third International Workshop on the Evaluation of Systems for the Semantic Analysis of Text

pdf bib
Semantic role labeling with Boosting, SVMs, Maximum Entropy, SNOW, and Decision Lists
Grace Ngai | Dekai Wu | Marine Carpuat | Chi-Shing Wang | Chi-Yung Wang
Proceedings of SENSEVAL-3, the Third International Workshop on the Evaluation of Systems for the Semantic Analysis of Text

pdf bib
Joining forces to resolve lexical ambiguity: East meets West in Barcelona
Richard Wicentowski | Grace Ngai | Dekai Wu | Marine Carpuat | Emily Thomforde | Adrian Packel
Proceedings of SENSEVAL-3, the Third International Workshop on the Evaluation of Systems for the Semantic Analysis of Text

2003

pdf bib
A Stacked, Voted, Stacked Model for Named Entity Recognition
Dekai Wu | Grace Ngai | Marine Carpuat
Proceedings of the Seventh Conference on Natural Language Learning at HLT-NAACL 2003

2002

pdf bib
Boosting for Named Entity Recognition
Dekai Wu | Grace Ngai | Marine Carpuat | Jeppe Larsen | Yongsheng Yang
COLING-02: The 6th Conference on Natural Language Learning 2002 (CoNLL-2002)

2000

pdf bib
An Information-Theory-Based Feature Type Analysis for the Modeling of Statistical Parsing
Zhifang Sui | Jun Zhao | Dekai Wu
Proceedings of the 38th Annual Meeting of the Association for Computational Linguistics

1999

pdf bib
An Information-Theoretic Empirical Analysis of Dependency-Based Feature Types for Word Prediction Models
Dekai Wu | Jun Zhao | Zhifang Sui
1999 Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora

pdf bib
Automatically Merging Lexicons that have Incompatible Part-of-Speech Categories
Daniel Ka-Leung Chan | Dekai Wu
1999 Joint SIGDAT Conference on Empirical Methods in Natural Language Processing and Very Large Corpora

1998

pdf bib
Machine Translation with a Stochastic Grammatical Channel
Dekai Wu | Hongsing Wong
COLING 1998 Volume 2: The 17th International Conference on Computational Linguistics

pdf bib
Machine Translation with a Stochastic Grammatical Channel
Dekai Wu | Hongsing Wong
36th Annual Meeting of the Association for Computational Linguistics and 17th International Conference on Computational Linguistics, Volume 2

1997

pdf bib
Dealing with Multilinguality in a Spoken Language Query Translator
Pascale Fung | Bertram Shi | Dekai Wu | Lain Wai Bun | Wong Shuen Kong
Spoken Language Translation

pdf bib
Stochastic Inversion Transduction Grammars and Bilingual Parsing of Parallel Corpora
Dekai Wu
Computational Linguistics, Volume 23, Number 3, September 1997

1996

pdf bib
A Polynomial-Time Algorithm for Statistical Machine Translation
Dekai Wu
34th Annual Meeting of the Association for Computational Linguistics

pdf bib
Parsing Chinese With an Almost-Context-Free Grammar
Xuanyin Xia | Dekai Wu
Conference on Empirical Methods in Natural Language Processing

pdf bib
Panel: Next steps in MT research
Lynn Carlson | Jaime Carbonell | David Farwell | Pierre Isabelle | Jackie Murgida | John O’Hara | Dekai Wu
Conference of the Association for Machine Translation in the Americas

1995

pdf bib
Using Brackets to Improve Search for Statistical Machine Translation
Dekai Wu | Cindy Ng
Proceedings of the 10th Pacific Asia Conference on Language, Information and Computation

pdf bib
Trainable Coarse Bilingual Grammars for Parallel Text Bracketing
Dekai Wu
Third Workshop on Very Large Corpora

pdf bib
An Algorithm for Simultaneously Bracketing Parallel Texts by Aligning Words
Dekai Wu
33rd Annual Meeting of the Association for Computational Linguistics

1994

pdf bib
Aligning a Parallel English-Chinese Corpus Statistically With Lexical Criteria
Dekai Wu
32nd Annual Meeting of the Association for Computational Linguistics

pdf bib
Book Reviews: Statistically-Driven Computer Grammars of English: The IBM/Lancaster Approach
Dekai Wu
Computational Linguistics, Volume 20, Number 3, September 1994

pdf bib
Learning an English-Chinese Lexicon from a Parallel Corpus
Dekai Wu | Xuanyin Xia
Proceedings of the First Conference of the Association for Machine Translation in the Americas

pdf bib
Improving Chinese Tokenization With Linguistic Filters on Statistical Lexical Acquisition
Dekai Wu | Pascale Fung
Fourth Conference on Applied Natural Language Processing

1990

pdf bib
Probabilistic Unification-Based Integration Of Syntactic and Semantic Preferences For Nominal Compounds
Dekai Wu
COLING 1990 Volume 2: Papers presented to the 13th International Conference on Computational Linguistics

1988

pdf bib
The Berkeley Unix Consultant Project
Robert Wilensky | David N. Chin | Marc Luria | James Martin | James Mayfield | Dekai Wu
Computational Linguistics, Volume 14, Number 4, December 1988, LFP: A Logic for Linguistic Descriptions and an Analysis of its Complexity