Abstract
In this paper, we propose a general framework for multi-accent speech recognition that combines Multi-level Adaptive Network (MLAN) and automatic model selection system based on accent classification. This framework solves the problem of domain mismatch between standard Mandarin and accent data and makes full use of limited accent data. The effectiveness of the proposed method was evaluated on two typical Chinese accent data, namely Shanghai and Chongqing accents. Results show higher performance of the framework on multi-accent speech recognition compared to GMM-HMM systems with prior accent label knowledge, with up to 3.89% CER (Character Error Rate) reduction on Chongqing accent test set and 1.71% on Shanghai accent test set.
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.
