DocumentCode
2019472
Title
Learning speech semantics with keyword classification trees
Author
Kuhn, Roland ; de Mori, Renato
Volume
2
fYear
1993
fDate
27-30 April 1993
Firstpage
55
Abstract
A linguistic analyzer based on KCTs (keyword classification trees) was trained on sentences from the ATIS (Air Travel Information System) air travel task and incorporated into the system (CHANEL) built at CRIM (Centre de Recherche Informatique de Montreal) for the Nov. 1992 ATIS benchmarks. Word sequences were processed by a local parser that identified semantically important noun phrases and then passed through a forest of KCTs, each responsible for generating a different aspect of the semantic representation. CHANEL attained a reasonable performance level, despite its heavy reliance on KCTs rather than on handcoded linguistic rules. The CRIM speech recognition system had a recognition rate of 88.9% words correct; CHANEL is clearly robust.<>
Keywords
grammars; learning (artificial intelligence); speech recognition; Air Travel Information System; keyword classification trees; linguistic analyzer; local parser; performance level; semantic representation; speech recognition system; speech semantics;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing, 1993. ICASSP-93., 1993 IEEE International Conference on
Conference_Location
Minneapolis, MN, USA
ISSN
1520-6149
Print_ISBN
0-7803-7402-9
Type
conf
DOI
10.1109/ICASSP.1993.319228
Filename
319228
Link To Document