Searching for authors named "Miles Osborne" – sorted by Relevance.

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46 documents found, showing 1 through 10. Next 10 →

Estimation of Stochastic Attribute-Value Grammars using an Informative Sample
by Miles Osborne — 2000
…We argue that some of the computational complexity associated with estimation of stochastic attribute- value grammars can be reduced by training upon an informative subset of the full training set. Results using the t)arsed Wall Street Journal tort)us show that in some circumstances, it is possible …
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Just how good is maximum entropy? An empirical investigation using ensembles of MEMD models for attribute-value grammars
by Miles Osborne
…Maximum entropy has been theoretically argued as being the principled way to estimate models that are only partially determined by some set of empirically observed constraints. However, such arguments hinge upon large sample behaviour, and it is unclear how well maximum entropy performs when this as…
Cited by 3 (0 self) – Add To MetaCart

Can Punctuation Help Learning?
by Miles Osborne — 1996 — In IJCAI95 Workshop on New Approaches to Learning for Natural Language Processing
…The quality of learnt natural language grammars can be enhanced by exploiting the linguistic devices that comprise a corpus. This paper considers one such device, namely punctuation. After briefly considering the linguistics of punctuation, a model capturing some of these properties is presente…
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Shallow Parsing as Part-of-Speech Tagging
by Miles Osborne — 2000
…Treating shallow parsing as part-of-speech tagging yields results comparable with other, more elaborate approaches. Using the CoNLL 2000 training and testing material, our best model had an accuracy of 94.88%, with an overall FB1 score of 91.94%. The individual FB1 scores for NPs were 92.19%, VPs 92…
Cited by 6 (0 self) – Add To MetaCart

MDL-based DCG Induction for NP Identification
by Miles Osborne — 1999
…We introduce a learner capable of automatically extend- ing large, manually written natural language Definite Clause Grammars with missing syntactic rules. It is based upon the Minimum Description Length principle, and can be trained upon either just raw text, or else raw text additionally annotated…
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DCG Induction using MDL and Parsed Corpora
by Miles Osborne — 1999 — Learning Language in Logic, pages 63–71, Bled,Slovenia
…We show how partial models of natural language syntax (manually written DCGs, with parameters estimated from a parsed corpus) can be automatically extended when trained upon raw text (using MDL). We also show how we can use a parsed corpus as an alternative constraint upon learning. Empirical ev…
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Minimisation, Indifference and Statistical Language Learning
by Miles Osborne — 1997
…When applied to probabilistic categorial grammar learning, the Minimum Description Length principle outperforms Maximum Likelihood Estimation. Smoothing does not bridge the gap between the two approaches. …
Cited by 2 (0 self) – Add To MetaCart

Predicting Success in Machine Translation
by Alexandra Birch, Miles Osborne
…The performance of machine translation systems varies greatly depending on the source and target languages involved. Determining the contribution of different characteristics of language pairs on system performance is key to knowing what aspects of machine translation to improve and which are irrele…
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Modelling lexical redundancy for machine translation
by David Talbot, Miles Osborne — 2006 — In Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics
…Certain distinctions made in the lexicon of one language may be redundant when translating into another language. We quantify redundancy among source types by the similarity of their distributions over target types. We propose a languageindependent framework for minimising lexical redundancy that ca…
Cited by 4 (1 self) – Add To MetaCart

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