Analysis and Tuning of a Voice Assistant System for Dysfluent Speech

@article{Mitra2021AnalysisAT,
  title={Analysis and Tuning of a Voice Assistant System for Dysfluent Speech},
  author={Vikramjit Mitra and Zifang Huang and Colin S. Lea and Lauren Tooley and Sarah Wu and Darren Botten and Ashwin Palekar and Shrinath Thelapurath and Panayiotis G. Georgiou and Sachin S. Kajarekar and Jefferey Bigham},
  journal={ArXiv},
  year={2021},
  volume={abs/2106.11759}
}
Dysfluencies and variations in speech pronunciation can severely degrade speech recognition performance, and for many individuals with moderate-to-severe speech disorders, voice op-erated systems do not work. Current speech recognition systems are trained primarily with data from fluent speakers and as a consequence do not generalize well to speech with dysfluencies such as sound or word repetitions, sound prolongations, or audible blocks. The focus of this work is on quantitative analysis of a… 

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