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Automated Speech Audiometry for Integrated Voice Over Internet Protocol Communication Services.

Tobias BrunsJasper OosterMatthias StennesJan Rennies
Published in: American journal of audiology (2022)
= .93) between the fully automatic and "laboratory" conditions, with a constant bias of about 1 dB indicating a linear shift of the data without affecting the distribution around the mean. The individual impact of the different system degradations on SRTs could be quantified Conclusions: This study provides a proof of concept for automated ASR-based SRT measurements over VoIP systems for speech audiometric testing in real communication systems, as it produced results comparable to traditional laboratory settings for this group of 16 normal-hearing subjects. This makes VoIP services a promising candidate for speech audiometric testing in real communication systems.
Keyphrases
  • deep learning
  • machine learning
  • hearing loss
  • healthcare
  • primary care
  • high throughput
  • mental health
  • randomized controlled trial
  • big data
  • electronic health record
  • artificial intelligence
  • health information