Christer Samuelsson


2012

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HAL: Challenging Three Key Aspects of IBM-style Statistical Machine Translation
Christer Samuelsson
Proceedings of the 10th Conference of the Association for Machine Translation in the Americas: Research Papers

The IBM schemes use weighted cooccurrence counts to iteratively improve translation and alignment probability estimates. We argue that: 1) these cooccurrence counts should be combined differently to capture word correlation; 2) alignment probabilities adopt predictable distributions; and 3) consequently, no iteration is needed. This applies equally well to word-based and phrase-based approaches. The resulting scheme, dubbed HAL, outperforms the IBM scheme in experiments.

2007

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Book Reviews: Inductive Dependency Parsing, by Joakim Nivre
Christer Samuelsson
Computational Linguistics, Volume 33, Number 2, June 2007

2000

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A Statistical Theory of Dependency Syntax
Christer Samuelsson
COLING 2000 Volume 2: The 18th International Conference on Computational Linguistics

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Experiments with Corpus-based LFG Specialization
Nicola Cancedda | Christer Samuelsson
Sixth Applied Natural Language Processing Conference

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Corpus-Based Grammar Specialization
Nicola Cancedda | Christer Samuelsson
Fourth Conference on Computational Natural Language Learning and the Second Learning Language in Logic Workshop

1998

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Linguistic Theory in Statistical Language Learning
Christer Samuelsson
New Methods in Language Processing and Computational Natural Language Learning

1997

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A Left-to-right Tagger for Word Graphs
Christer Samuelsson
Proceedings of the Fifth International Workshop on Parsing Technologies

An algorithm is presented for tagging input word graphs and producing output tag graphs that are to be subjected to further syntactic processing. It is based on an extension of the basic HMM equations for tagging an input word string that allows it to handle word-graph input, where each arc has been assigned a probability. The scenario is that of some word-graph source, e.g., an acoustic speech recognizer, producing the arcs of a word graph, and the tagger will in turn produce output arcs, labelled with tags and assigned probabilities. The processing as done entirely left-to-right, and the output tag graph is constructed using a minimum of lookahead, facilitating real-time processing.

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Comparing a Linguistic and a Stochastic Tagger
Christer Samuelsson | Atro Voutilainen
35th Annual Meeting of the Association for Computational Linguistics and 8th Conference of the European Chapter of the Association for Computational Linguistics

1996

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Relating Turing’s Formula and Zipf’s Law
Christer Samuelsson
Fourth Workshop on Very Large Corpora

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Handling Sparse Data by Successive Abstraction
Christer Samuelsson
COLING 1996 Volume 2: The 16th International Conference on Computational Linguistics

1995

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A Novel Framework for Reductionistic Statistical Parsing
Christer Samuelsson
Proceedings of the Fourth International Workshop on Parsing Technologies

A reductionistic statistical framework for part-of-speech tagging and surface syntactic parsing is presented that has the same expressive power as the highly successful Constraint Grammar approach, see [Karlsson et al. 1995]. The structure of the Constraint Grammar rules allows them to be viewed as conditional probabilities that can be used to update the lexical tag probabilities, after which low-probability tags are repeatedly removed. Experiments using strictly conventional information sources on the Susanne and Teleman corpora indicate that the system performs as well as a traditional HMM-based part-of-speech tagger, yielding state-of-the-art results. The scheme also enables using the same information sources as the Constraint Grammar approach, and the hope is that it can improve on the performance of both statistical taggers and surface-syntactic analyzers.

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Tagging the Teleman Corpus
Thorsten Brants | Christer Samuelsson
Proceedings of the 10th Nordic Conference of Computational Linguistics (NODALIDA 1995)

1994

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Grammar Specialization Through Entropy Thresholds
Christer Samuelsson
32nd Annual Meeting of the Association for Computational Linguistics

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Notes on LR Parser Design
Christer Samuelsson
COLING 1994 Volume 1: The 15th International Conference on Computational Linguistics

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Clustering Sentences – Making Sense of Synonymous Sentences
Jussi Karlgren | Björn Gambäck | Christer Samuelsson
Proceedings of the 9th Nordic Conference of Computational Linguistics (NODALIDA 1993)

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Morphological Tagging Based Entirely on Bayesian Inference
Christer Samuelsson
Proceedings of the 9th Nordic Conference of Computational Linguistics (NODALIDA 1993)

1993

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A Speech to Speech Translation System Built From Standard Components
Manny Rayner | Hiyan Alshawi | Ivan Bretan | David Carter | Vassilios Digalakis | Bjorn Gamback | Jaan Kaja | Jussi Karlgren | Bertil Lyberg | Steve Pulman | Patti Price | Christer Samuelsson
Human Language Technology: Proceedings of a Workshop Held at Plainsboro, New Jersey, March 21-24, 1993

1992

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Ebl²: An Approach to Automatic Lexical Acquisition
Lars Asker | Bjorn Gamback | Christer Samuelsson
COLING 1992 Volume 4: The 14th International Conference on Computational Linguistics

1990

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Using Explanation-Based Learning to Increase Performance in a Large-Scale NL Query System
Manny Rayner | Christer Samuelsson
Speech and Natural Language: Proceedings of a Workshop Held at Hidden Valley, Pennsylvania, June 24-27,1990