Titlebook: Robustness in Language and Speech Technology; Jean-Claude Junqua,Gertjan Noord Book 2001 Springer Science+Business Media B.V. 2001 Parsing

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Cardioversion

Robust Parsing of Word Graphs,word graph, provided an appropriate multi-dimensional score function is defined..Finally, a number of techniques is discussed which approximate the fully general search algorithm and experimental results are provided indicating that efficient approximations are possible with little or no reduction in concept accuracy.

RALES

Introduction,s concerning such things as timetables for public transportation. For example, you might ask the system the departure time of a train from Brussels to Amsterdam, specifying that you wish to arrive in Amsterdam at 11. Before proceeding to answer your query such a system will probably ask you on which

沒有希望

dominant

Speaker Compensation in Automatic Speech Recogniton,en the training and testing conditions are similar. However, the word accuracy dramatically degrades if the training and testing conditions differ: Well-known factors that affect the word error rate (WER) are background noise and channel and speaker variability..This chapter deals with the latter (i

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Robustness in Statistical Language Modeling: Review and Perspectives,ced on the spoken utterances, or more generally when the lexical, syntactic, or semantic characteristics of the discourse in the training and testing tasks differ. Obstacles to robustness involve the dual issues of model coverage and parameter reliability, which are intricately related to the qualit

JEER

heirloom

Regular Approximation of Context-Free Grammars through Transformation,s to any context-free grammar and guarantees that the result can be compiled into a finite automaton. The resulting grammar contains at most one new nonterminal for any nonterminal symbol of the input grammar. The result thus remains readable and if necessary modifiable. We extend the approximation

Chromatic

OTHER

Robust Parsing and Beyond,actually produced by end-users in various situations..While early work in robust analysis dates back to the seventies, the topic has recently gained broader attention, due to the large quantities of textual data now available in electronic form (e.g. technical documentation, news, web pages, email,