Abstract
Recent success of mobile personal assistants deeply relies on the advancement in statistical automatic speech recognition (ASR) and spoken language understanding (SLU) technologies. This article describes practical design of ASR and SLU systems for “Shabette Concier”, a voice-based personal assistant application commercially released by NTT docomo in Japan in March 2012. Utilization of a large amount of field speech data gathered from the actual service is focused and the potential of big data is discussed.
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.
