New Technique for Handling ASR Errors at the Semantic Level in Spoken Dialogue Systems View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2011-08-12

AUTHORS

Ramón López-Cózar , Zoraida Callejas , David Griol , José F. Quesada

ABSTRACT

This paper proposes a new technique to develop more robust spoken dialogue systems, which aims to repair incorrect semantic representations obtained by the systems due to ASR errors. To do so, it relies on a training stage that takes into account previous system misunderstandings for each dialogue state. Experiments have been carried out employing two systems (Saplen and Viajero) previously developed in our lab, which employ a prompt-independent language model and several prompt-dependent language models for ASR. The results, obtained for a corpus of 20,000 simulated dialogues, show that the technique enhances system performance for both kinds of language model, especially for the prompt-independent language model. More... »

PAGES

17-29

Book

TITLE

Proceedings of the Paralinguistic Information and its Integration in Spoken Dialogue Systems Workshop

ISBN

978-1-4614-1334-9
978-1-4614-1335-6

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-1-4614-1335-6_4

DOI

http://dx.doi.org/10.1007/978-1-4614-1335-6_4

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1022505057


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