Abstract
Here, we propose a small-footprint speaker-independent, multilingual system for isolated word recognition of Mandarin, Cantonese, and English. The baseline system got very promising results without any phoneme shared between different languages. By sharing phonemes, the memory and computational complexity was reduced by about 40%. Nonnative, accented speech recognition and mixed language words support are the distinguishing features of our system. Automatic language identification (LID) is one of the key elements in language-independent automatic speech recognition (ASR) systems. LID perfomance is also analyzed in addition to the engine performance of the proposed system. Supervised Bayesian online adaptation was proved to be effective in compensation for accent mismatch, environment mismatch, as well as for modeling inaccuracy introduced by combined training.
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.
