Available Technologies
# of Displayed Technologies: 3 / 3
Applied Category Filter (Click To Remove): Human/Machine Interface
Joint Activity Testing (JAT): A Testing & Evaluation Methodology for Human-Machine Teams
TS-068443 —
In high-stakes industries, the integration of humans and advanced automation systems demands evaluation methods that reliably predict performance under varying challenges. Current testing methods often focus on individual components, failing to assess how human-machine teams operate as a unit, par…
- College: College of Engineering (COE)
- Inventors: Morey, Dane; Rayo, Michael
- Licensing Officer: Giles, David
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: Dahlman, Jason "Jay"
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: Dahlman, Jason "Jay"
