Free Advances in Probabilistic and Other Parsing Technologies (Text Speech and Language Technology)

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Book Details :
Published on: 2010-12-05
Released on: 2010-12-05
Original language: English

Parsing technology is concerned with finding syntactic structure in language. In parsing we have to deal with incomplete and not necessarily accurate formal descriptions of natural languages. Robustness and efficiency are among the main issuesin parsing. Corpora can be used to obtain frequency information about language use. This allows probabilistic parsing, an approach that aims at both robustness and efficiency increase. Approximation techniques, to be applied at the level of language description, parsing strategy, and syntactic representation, have the same objective. Approximation at the level of syntactic representation is also known as underspecification, a traditional technique to deal with syntactic ambiguity. In this book new parsing technologies are collected that aim at attacking the problems of robustness and efficiency by exactly these techniques: the design of probabilistic grammars and efficient probabilistic parsing algorithms, approximation techniques applied to grammars and parsers to increase parsing efficiency, and techniques for underspecification and the integration of semantic information in the syntactic analysis to deal with massive ambiguity. The book gives a state-of-the-art overview of current research and development in parsing technologies. In its chapters we see how probabilistic methods have entered the toolbox of computational linguistics in order to be applied in both parsing theory and parsing practice. The book is both a unique reference for researchers and an introduction to the field for interested graduate students. TTIC Courses TTIC 31010 - Algorithms (CMSC 37000) 100 units. Chuzhoy Julia and Makarychev Yury. This is a graduate level course on algorithms with the emphasis on central ... Computer Science Stanford University Bachelor of Science in Computer Science. The department offers both a major in Computer Science and a minor in Computer Science. Further information is available in ... Machine Learning Group Publications - University of Cambridge Matej Balog Balaji Lakshminarayanan Zoubin Ghahramani Daniel M. Roy and Yee Whye Teh. The Mondrian kernel. In 32nd Conference on Uncertainty in Artificial ... Microsoft Research Emerging Technology Computer and ... Research Research. Research Home; Research areas. Algorithms Artificial intelligence Computer systems and networking Publications Page - Cambridge Machine Learning Group [ full BibTeX file] 2017 2016. Matej Balog Alexander L. Gaunt Marc Brockschmidt Sebastian Nowozin and Daniel Tarlow. DeepCoder: Learning to write programs. Terminology extraction - Wikipedia Terminology extraction (also known as term extraction glossary extraction term recognition or terminology mining) is a subtask of information extraction. Speech recognition - Wikipedia Speech recognition (SR) is the inter-disciplinary sub-field of computational linguistics that develops methodologies and technologies that enables the recognition and ... 18. The WEKA Data Mining Software: an Update More than twelve years have elapsed since the first public release of WEKA. In that time the software has been rewritten entirely from scratch evolved substantially ... Publications - ImageNet Citations and publications Presentation and Slides. L. Fei-Fei and O. Russakovsky Analysis of Large-Scale Visual Recognition Bay Area Vision Meeting October 2013 ... An Introduction to text-to-speech synthesis A Short Introduction to Text-to-Speech Synthesis. by Thierry Dutoit. TTS research team TCTS Lab. Abstract. I try to give here a short but comprehensive introduction ...
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