@inproceedings{31fbe013b47444bdba662f772e3d2913,
title = "Comparing grammar-based and robust approaches to speech understanding: A case study",
abstract = "Previous work has demonstrated the success of statistical language models when enough training data is available [1], but despite that, grammar-based systems are proving the preferred choice in successful commercial systems such as HeyAnita [2], BeVocal [3] and Tellme [4], largely due to the difficulty involved in obtaining a corpus of training data. Here we trained an SLM on data obtained using a grammar-based system and compared the performance of the two systems with regards to recognition. We also parsed the output of the SLM using a robust parser and compared the accuracy of the semantic output of the systems. The SLM/robust parser showed considerable improvement on unconstrained input, and similar precision/recall (per slot value) on utterances provided by trained users.",
author = "Sylvia Knight and Genevieve Gorrell and Manny Rayner and David Milward and Rob Koeling and Ian Lewin",
year = "2001",
language = "Ingl{\'e}s",
series = "EUROSPEECH 2001 - SCANDINAVIA - 7th European Conference on Speech Communication and Technology",
publisher = "International Speech Communication Association",
pages = "1779--1782",
editor = "Borge Lindberg and Henrik Benner and Paul Dalsgaard and Zheng-Hua Tan",
booktitle = "EUROSPEECH 2001 - SCANDINAVIA - 7th European Conference on Speech Communication and Technology",
note = "7th European Conference on Speech Communication and Technology - Scandinavia, EUROSPEECH 2001 ; Conference date: 03-09-2001 Through 07-09-2001",
}