@inproceedings{wang2001grammar,
author = {Wang, Ye-Yi and Acero, Alex},
title = {Grammar Learning for Spoken Language Understanding},
booktitle = {IEEE Workshop on Automatic Speech Recognition and Understanding},
year = {2001},
month = {January},
abstract = {Many state-of-the-art conversational systems use semantic-based robust understanding and manually derived grammars, a very time-consuming and error-prone process. This paper describes a machine-aided grammar authoring system that enables a programmer to develop rapidly a high quality grammar for conversational systems. This is achieved with a combination of domain-specific semantics, a library grammar, syntactic constraints and a small number of example sentences that have been semantically annotated. Our experiments show that the learned semantic grammars consistently outperform manually authored grammars, requiring much less authoring load.},
publisher = {Institute of Electrical and Electronics Engineers, Inc.},
url = {http://approjects.co.za/?big=en-us/research/publication/grammar-learning-for-spoken-language-understanding/},
pages = {292},
edition = {IEEE Workshop on Automatic Speech Recognition and Understanding},
}