SoundWatch: Exploring Smartwatch-based Deep Learning Approaches to Support Sound Awareness for Deaf and Hard of Hearing Users

@article{Jain2020SoundWatchES,
  title={SoundWatch: Exploring Smartwatch-based Deep Learning Approaches to Support Sound Awareness for Deaf and Hard of Hearing Users},
  author={Dhruv Jain and Hung Ngo and Pratyush Patel and Steven M. Goodman and Leah Findlater and Jon Froehlich},
  journal={The 22nd International ACM SIGACCESS Conference on Computers and Accessibility},
  year={2020}
}
  • D. Jain, Hung Ngo, Jon Froehlich
  • Published 26 October 2020
  • Computer Science
  • The 22nd International ACM SIGACCESS Conference on Computers and Accessibility
Smartwatches have the potential to provide glanceable, always-available sound feedback to people who are deaf or hard of hearing. In this paper, we present a performance evaluation of four low-resource deep learning sound classification models: MobileNet, Inception, ResNet-lite, and VGG-lite across four device architectures: watch-only, watch+phone, watch+phone+cloud, and watch+cloud. While direct comparison with prior work is challenging, our results show that the best model, VGG-lite… 

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