# of Displayed Technologies: 5 / 5


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Machine-Learning Algorithm for Improved Speech Intelligibility in Noise
TS-042266 — A monaural machine-learning algorithm for classifying time-frequency units in an unknown signal, which results in marked speech-intelligibly improvements in noisy signals.
A primary complaint of hearing-impaired (HI) listeners is poor speech recognition in background noise. This issue can be quite debilitating and persists despite considerable efforts to improve hearing technology. Despite considerable effort, monaural (single-microphone) algorithms capable of incre…
  • College: College of Arts & Sciences
  • Inventors: Healy, Eric; Vasko, Jordan
  • Licensing Officer: Hong, Dongsung

Machine-Learning Algorithm for Improved Speech Intelligibility in Noise
TS-042266 — A monaural machine-learning algorithm for classifying time-frequency units in an unknown signal, which results in marked speech-intelligibly improvements in noisy signals.
A primary complaint of hearing-impaired (HI) listeners is poor speech recognition in background noise. This issue can be quite debilitating and persists despite considerable efforts to improve hearing technology. Despite considerable effort, monaural (single-microphone) algorithms capable of incre…
  • College: College of Arts & Sciences
  • Inventors: Healy, Eric; Vasko, Jordan
  • Licensing Officer: Hong, Dongsung

Machine-Learning Algorithm for Improved Speech Intelligibility in Noise
TS-038074 — A monaural machine-learning algorithm for classifying time-frequency units in an unknown signal, which results in marked speech-intelligibly improvements in noisy signals.
Wireless carriers receive daily complaints about poor speech recognition in background noise during calls and are constantly looking for methods to improve especially in light of recent forays into VOIP. The ability to discriminate between speech and noise in an audio signal then is an extremely i…
  • College: College of Arts & Sciences
  • Inventors: Healy, Eric; Vasko, Jordan
  • Licensing Officer: Hong, Dongsung

Machine-Learning Algorithm for Improved Speech Intelligibility in Noise
TS-038074 — A monaural machine-learning algorithm for classifying time-frequency units in an unknown signal, which results in marked speech-intelligibly improvements in noisy signals.
Wireless carriers receive daily complaints about poor speech recognition in background noise during calls and are constantly looking for methods to improve especially in light of recent forays into VOIP. The ability to discriminate between speech and noise in an audio signal then is an extremely i…
  • College: College of Arts & Sciences
  • Inventors: Healy, Eric; Vasko, Jordan
  • Licensing Officer: Hong, Dongsung

Multi-carrier processing in auditory prosthetic devices
TS-014871 — Encoding strategy for improvement of speech understanding in a noisy environment for audiotory prosthetic devices.
There are about 275 million adults globally with moderate to severe hearing loss and 360 million adults with mild hearing loss. The current solutions to allow these people to hear better include hearing aids, hearing loss counseling, cochlear implants, alerting devices, and other communication aid…
  • College: College of Arts & Sciences
  • Inventors: Apoux, Frederic; Healy, Eric
  • Licensing Officer: Hong, Dongsung

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