Statistical Phrase-Based Translation
- Philipp Koehn, F. Och, D. Marcu
- Computer ScienceNorth American Chapter of the Association for…
- 27 May 2003
The empirical results suggest that the highest levels of performance can be obtained through relatively simple means: heuristic learning of phrase translations from word-based alignments and lexical weighting of phrase translation.
Building a Discourse-Tagged Corpus in the Framework of Rhetorical Structure Theory
- Lynn Carlson, D. Marcu, Mary Ellen Okurovsky
- SociologySIGDIAL Workshop
- 1 September 2001
Working in the framework of Rhetorical Structure Theory, a large annotated resource with very high consistency is created, using a well-defined methodology and protocol to enable researchers to develop empirically grounded, discourse-specific applications.
The Theory and Practice of Discourse Parsing and Summarization
- D. Marcu
- Sociology
- 13 November 2000
This book documents the first serious attempt to construct automatically and use nonsemantic computational structures for text summarization and develops a semantics-free theoretical framework that is both general enough to be applicable to naturally occurring texts and concise enough to facilitate an algorithmic approach to discourse analysis.
What’s in a translation rule?
- Michel Galley, Mark Hopkins, Kevin Knight, D. Marcu
- Computer ScienceNorth American Chapter of the Association for…
- 2004
The theory is used to introduce a linear algorithm that can be used to derive from word-aligned, parallel corpora the minimal set of syntactically motivated transformation rules that explain human translation data.
Scalable Inference and Training of Context-Rich Syntactic Translation Models
- Michel Galley, Jonathan Graehl, I. Thayer
- Computer ScienceAnnual Meeting of the Association for…
- 17 July 2006
This paper takes the framework for acquiring multi-level syntactic translation rules of (Galley et al., 2004) from aligned tree-string pairs, and presents two main extensions of their approach: instead of merely computing a single derivation that minimally explains a sentence pair, a large number of derivations that include contextually richer rules, and account for multiple interpretations of unaligned words.
Sentence Level Discourse Parsing using Syntactic and Lexical Information
- Radu Soricut, D. Marcu
- Sociology, Computer ScienceNorth American Chapter of the Association for…
- 27 May 2003
Two probabilistic models that can be used to identify elementary discourse units and build sentence-level discourse parse trees are introduced and shown to be sophisticated enough to yield discourse trees at an accuracy level that matches near-human levels of performance.
Search-based structured prediction
- Hal Daumé, J. Langford, D. Marcu
- Computer ScienceMachine-mediated learning
- 1 June 2009
Searn is an algorithm for integrating search and learning to solve complex structured prediction problems such as those that occur in natural language, speech, computational biology, and vision and comes with a strong, natural theoretical guarantee: good performance on the derived classification problems implies goodperformance on the structured prediction problem.
Improving Machine Translation Performance by Exploiting Non-Parallel Corpora
- D. Munteanu, D. Marcu
- Computer ScienceComputational Linguistics
- 1 December 2005
A maximum entropy classifier is trained that, given a pair of sentences, can reliably determine whether or not they are translations of each other and can be applied with great benefit to language pairs for which only scarce resources are available.
An Unsupervised Approach to Recognizing Discourse Relations
- D. Marcu, Abdessamad Echihabi
- Computer ScienceAnnual Meeting of the Association for…
- 6 July 2002
It is shown that discourse relation classifiers trained on examples that are automatically extracted from massive amounts of text can be used to distinguish between some of these relations with accuracies as high as 93%, even when the relations are not explicitly marked by cue phrases.
Summarization beyond sentence extraction: A probabilistic approach to sentence compression
- Kevin Knight, D. Marcu
- Computer ScienceArtificial Intelligence
- 1 July 2002
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