ASTER: Automatic Speech Recognition System Accessibility Testing for Stutterers
Author:
Affiliation:
1. Nanyang Technological University
2. University of New South Wales
3. Meta AI
4. University of Southern California
5. Institute of Information Engineering, Chinese Academy of Sciences
6. The University of Tokyo
Funder
National Research Foundation, Singapore
NRF
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10298258/10298286/10298290.pdf?arnumber=10298290
Reference53 articles.
1. Enhancing asr for stuttered speech with limited data using detect and pass;shonibare;ArXiv,2022
2. StutterNet: Stuttering Detection Using Time Delay Neural Network
3. Web Accessibility Testing for Deaf: Requirements and Approaches for Automation
4. Automated Accessibility Testing of Mobile Apps
5. Cerebro: context-aware adaptive fuzzing for effective vulnerability detection
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1. A CNN-based Stutter Detection Using MFCC Features with Binary Cross-Entropy Loss Function;2024 IEEE International Conference on Contemporary Computing and Communications (InC4);2024-03-15
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