Abstract
Utterance verification provides the speech recognition system a user-friendly interaction. However, small-vocabulary system using DTW algorithm cannot afford HMM based utterance verification. So, to equip the DTW based recognizer with effective utterance verification becomes an essential problem in a low computational application. We proposed a new utterance verification method, combining both statistic and distance measure capability, to map DTW distance to a certain likelihood. The likelihood as a confidence measure performs a good ability of both speech recognition and utterance verification. With a test set of fifteen words, at 5.24% false rejection, the verification method brought on 10.44% false alarm rate and 93.61% accuracy. Furthermore, 94.76% out-of-vocabulary utterances were correctly rejected.
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.
