Title | Improving spoken dialogue understanding using phonetic mixture models. |
Publication Type | Conference Proceedings |
Year of Conference | 2011 |
Authors | Wang, W. Y., R. Artstein, A. Leuski, and D. R. Traum |
Conference Name | Proceedings of the Twenty-Fourth International Florida Artificial Intelligence Research Society Conference |
Pagination | 329-334 |
Date Published | May 2011 |
Conference Location | Palm Beach, Florida |
Abstract | Augmenting word tokens with a phonetic representation, derived from a dictionary, improves the performance of a Natural Language Understanding component that interprets speech recognizer output: we observed a 5% to 7% reduction in errors across a wide range of response return rates. The best performance comes from mixture models incorporating both word and phone features. Since the phonetic representation is derived from a dictionary, the method can be applied easily without the need for integration with a specific speech recognizer. The method has similarities with autonomous (or bottom-up) psychological models of lexical access, where contextual information is not integrated at the stage of auditory perception but rather later. |
URL | http://www.aaai.org/ocs/index.php/FLAIRS/FLAIRS11/paper/viewFile/2563/3049 |