Fitting class-based language models into weighted finite-state transducer framework

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F03%3A00000214" target="_blank" >RIV/49777513:23520/03:00000214 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Result language
angličtina
Original language name
Fitting class-based language models into weighted finite-state transducer framework
Original language description
In our paper we propose a general way of incorporating class-based language models with many-to-many word-to-class mapping into the finite-state transducer (FST) framework. Since class-based models alone usually do not improve the recognition accuracy, we also present a method for an efficient language model combination. An example of a word-to-class mapping based on morphological tags is also given. Several word-based and tag-based language models are tested in the task of transcribing Czech broadcastnews. Results show that class-based models help to achieve a moderate improvement in recognition accuracy.
Czech name
Fitting class-based language models into weighted finite-state transducer framework
Czech description
Článek pojednává o jazykovém modelování, které je založeno na třídách a je přizpůsobeno využití v síti transducerů.

Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
JD - Use of computers, robotics and its application
OECD FORD branch
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Project
<a href="/en/project/LN00A063" target="_blank" >LN00A063: Centre of Computational Linguistics</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2003
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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