High level knowledge sources in usable speech recognition systems
Communications of the ACM
User models in dialog systems
An overview of the SPHINX speech recognition system
Readings in speech recognition
A computational model of expectation-driven mixed-initiative dialog processing
A computational model of expectation-driven mixed-initiative dialog processing
TINA: a natural language system for spoken language applications
Computational Linguistics
Design and development of spoken natural-language dialog parsing systems
Design and development of spoken natural-language dialog parsing systems
Plan Recognition in Natural Language Dialogue
Plan Recognition in Natural Language Dialogue
A dialog control algorithm and its performance
ANLC '92 Proceedings of the third conference on Applied natural language processing
Cues and control in expert-client dialogues
ACL '88 Proceedings of the 26th annual meeting on Association for Computational Linguistics
A natural language processing infrastructure for Turkish
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
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Several obstacles have prevented spoken natural-language systems from providing the required performance, including inflexibility, ineffective goal-seeking, and poor speech recognition. However, these problems can be circumvented by embedding the speech recognition technology within a dialog processing mechanism. Such a variable initiative dialog is a major advance that lets natural-language systems communicate effectively with novices and experts. Based on a theory of natural-language dialog that addresses these issues, the author has implemented a system that uses spoken natural language to help users repair electronic circuits. The integrated dialog-processing model combines a domain problem solver, a general subdialog mechanism, and knowledge about the user to provide timely and coherent assistance to the user. The robust parsing and language-understanding mechanism helps the system to correctly determine the meaning of utterances in spite of misrecognitions. Results indicate that commercial application of this technology is within reach, and should stimulate thought about how to further improve the quality of spoken natural-language interaction.