Title
Adaptive Speech Understanding for Intuitive Model-based Spoken Dialogues.
Abstract
In this paper we present three approaches towards adaptive speech understanding. The target system is a model-based Adaptive Spoken Dialogue Manager, the OwlSpeak ASDM. We enhanced this system in order to properly react on non-understandings in real-life situations where intuitive communication is required. OwlSpeak provides a model-based spoken interface to an Intelligent Environment depending on and adapting to the current context. It utilises a set of ontologies used as dialogue models that can be combined dynamically during runtime. Besides the benefits the system showed in practice, real-life evaluations also conveyed some limitations of the model-based approach. Since it is unfeasible to model all variations of the communication between the user and the system beforehand, various situations where the system did not correctly understand the user input have been observed. Thus we present three enhancements towards a more sophisticated use of the ontology-based dialogue models and show how grammars may dynamically be adapted in order to understand intuitive user utterances. The evaluation of our approaches revealed the incorporation of a lexical-semantic knowledgebase into the recognition process to be the most promising approach.
Year
Venue
Keywords
2012
LREC 2012 - EIGHTH INTERNATIONAL CONFERENCE ON LANGUAGE RESOURCES AND EVALUATION
Dialogue management,Failure prevention,Keyword spotting
Field
DocType
Citations 
Ontology (information science),Intelligent environment,Rule-based machine translation,Ontology,Computer science,Artificial intelligence,Natural language processing
Conference
1
PageRank 
References 
Authors
0.35
10
4
Name
Order
Citations
PageRank
Tobias Heinroth1569.56
Maximilian Grotz210.35
Florian Nothdurft36812.85
Wolfgang Minker4619108.61