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Supervised Learning of Response Grammars in a Spoken CALL System

Type of publication Peer-reviewed
Publikationsform Proceedings (peer-reviewed)
Author Rayner Manny, Baur Claudia, Chua Cathy, Tsourakis Nikos,
Project Designing and evaluating spoken dialogue based CALL systems
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Proceedings (peer-reviewed)

Title of proceedings Proc SLaTE workshop
Place Leipzig, Germany

Open Access

URL https://archive-ouverte.unige.ch/unige:73662
Type of Open Access Website

Abstract

We summarise experiments carried out using a system-initiative spoken CALL system, in which permitted responses to prompts are defined using a minimal formalism based on templates and regular expressions, and describe a simple structural learning algorithm that uses annotated data to update response definitions. Using 1 927 utterances of training data, we obtained a relative improvement of 20% in the system’s ability to react differentially to correct and incorrect input, measured on a previously unseen test set. The results are significant at p < 0:005.
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