Abstract
We have proposed an efficient approach to manage a dialog system using a weighted finite-state transducer (WFST) in which users? concept and system?s action tags are input and output of the transducer, respectively. A WFST for dialog management was automatically created using a corpus annotated with inter-change format (IF) consisting of dialog acts and argument which is an interlingua for machine translation. A word-to-concept WFST for spoken language understanding (SLU) was created using the same corpus. The scenario and SLU WFSTs acquired from the corpus were composed together and then optimized. We have confirmed the WFST automatically trained using the annotated corpus can manage dialog reasonably.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
