ACL 2004 - PDF Preprint Papers

ACL 2004 Meeting of the Association for Computational Linguistics

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2004

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Discriminative Language Modeling with Conditional Random Fields and the Perceptron Algorithm

13 years 6 months ago

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This paper describes discriminative language modeling for a large vocabulary speech recognition task. We contrast two parameter estimation methods: the perceptron algorithm, and a...

Brian Roark, Murat Saraclar, Michael Collins, Mark...

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Id	Views	Title	Status

1	198	Discriminative Language Modeling with Conditional Random Fields and the Perceptron Algorithm	claim
2	188	Statistical Machine Translation with Word- and Sentence-Aligned Parallel Corpora	claim
3	185	Applying Machine Learning to Chinese Temporal Relation Resolution	claim
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5	162	Collocation Translation Acquisition Using Monolingual Corpora	claim
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7	141	Balancing Clarity and Efficiency in Typed Feature Logic Through Delaying	claim
8	139	Generalized Multitext Grammars	claim
9	138	Using Conditional Random Fields to Predict Pitch Accents in Conversational Speech	claim
10	137	Dependency Tree Kernels for Relation Extraction	claim
11	135	Combining Acoustic and Pragmatic Features to Predict Recognition Performance in Spoken Dialogue Systems	claim
12	135	Multi-Engine Machine Translation with Voted Language Model	claim
13	134	Chinese Verb Sense Discrimination Using an EM Clustering Model with Rich Linguistic Features	claim
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15	129	Long-Distance Dependency Resolution in Automatically Acquired Wide-Coverage PCFG-Based LFG Approximations	claim
16	128	Finding Predominant Word Senses in Untagged Text	claim
17	127	Experiments in parallel-text based grammar induction	claim
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24	122	Predicting Student Emotions in Computer-Human Tutoring Dialogues	claim
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26	121	Incremental Parsing with the Perceptron Algorithm	claim
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33	113	Classifying Semantic Relations in Bioscience Texts	claim
34	112	Using Linguistic Principles to Recover Empty Categories	claim
35	112	Attention Shifting for Parsing Speech	claim
36	110	Relieving the data Acquisition Bottleneck in Word Sense Disambiguation	claim
37	109	Multi-Criteria-based Active Learning for Named Entity Recognition	claim
38	109	Annealing Techniques For Unsupervised Statistical Language Learning	claim
39	108	Head-Driven Parsing for Word Lattices	claim
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41	107	Mining Metalinguistic Activity in Corpora to Create Lexical Resources Using Information Extraction Techniques: the MOP System	claim
42	106	Inducing Frame Semantic Verb Classes from WordNet and LDOCE	claim
43	104	A Kernel PCA Method for Superior Word Sense Disambiguation	claim
44	103	Large-Scale Induction and Evaluation of Lexical Resources from the Penn-II Treebank	claim
45	103	Paragraph-, Word-, and Coherence-based Approaches to Sentence Ranking: A Comparison of Algorithm and Human Performance	claim
46	102	Error Mining for Wide-Coverage Grammar Engineering	claim
47	101	Computing Locally Coherent Discourses	claim
48	100	Statistical Machine Translation by Parsing	claim
49	99	Optimizing Typed Feature Structure Grammar Parsing through Non-Statistical Indexing	claim
50	96	Wrapping of Trees	claim
51	94	Improving IBM Word Alignment Model 1	claim
52	93	Data-Driven Strategies for an Automated Dialogue System	claim
53	93	Probabilistic Parsing Strategies	claim
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56	92	Generating Referring Expressions in Open Domains	claim
57	92	FLSA: Extending Latent Semantic Analysis with Features for Dialogue Act Classification	claim
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61	89	Enriching the Output of a Parser Using Memory-based Learning	claim
62	88	Creating Multilingual Translation Lexicons with Regional Variations Using Web Corpora	claim
63	88	Minimal Recursion Semantics as Dominance Constraints: Translation, Evaluation, and Analysis	claim
64	83	Evaluating Centering-Based Metrics of Coherence	claim
65	78	A TAG-based noisy-channel model of speech repairs	claim
66	75	Question Answering Using Constraint Satisfaction: QA-By-Dossier-With-Contraints	claim
67	71	Acquiring the Meaning of Discourse Markers	claim
68	71	An Alternative Method of Training Probabilistic LR Parsers	claim
69	52	Statistical Modeling for Unit Selection in Speech Synthesis	claim

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