Improved tactile speech robustness to background noise with a dual-path recurrent neural network noise-reduction method.

Many people with hearing loss struggle to understand speech in noisy environments, making noise robustness critical for hearing-assistive devices. Recently developed haptic hearing aids, which convert audio to vibration, can improve speech-in-noise performance for cochlear implant (CI) users and assist those unable to access hearing-assistive devices. They are typically body-worn rather than head-mounted, allowing additional space for batteries and microprocessors, and so can deploy more sophisticated noise-reduction techniques. The current study assessed whether a real-time-feasible dual-path recurrent neural network (DPRNN) can improve tactile speech-in-noise performance. Audio was converted to vibration on the wrist using a vocoder method, either with or without noise reduction. Performance was tested for speech in a multi-talker noise (recorded at a party) with a 2.5-dB signal-to-noise ratio. An objective assessment showed the DPRNN improved the scale-invariant signal-to-distortion ratio by 8.6 dB and substantially outperformed traditional noise-reduction (log-MMSE). A behavioural assessment in 16 participants showed the DPRNN improved tactile-only sentence identification in noise by 8.2%. This suggests that advanced techniques like the DPRNN could substantially improve outcomes with haptic hearing aids. Low-cost haptic devices could soon be an important supplement to hearing-assistive devices such as CIs or offer an alternative for people who cannot access CI technology.

Development and evaluation of a tablet-based diagnostic audiometer.

Objective: To develop and evaluate a software application capable of conducting Pure-Tone Audiometry tests in clinical practice. Design: We designed and developed a mobile software application for iPad devices that performs Pure-Tone Audiometry according to ANSI and IEC standards. The application is proposed to be operated by a trained audiologist inside a sound booth. No extra equipment is required. Hence, it updates the procedure by showing the versatility of the proposed system. Particularly, it provides manual and automated measurement, including air- and bone-conduction audiometry. Study sample: Twenty-nine participants-patients of Papageorgiou Hospital, Thessaloniki, Greece were tested, with all degrees of hearing sensitivity. Manual air- and bone-conduction Pure-Tone Audiometry was conducted inside a sound booth. Participants were tested with conventional audiometry and the audiometric application, in order to validate the tablet-based audiometer for measuring hearing thresholds. Results: The majority (90.9%) of air-conduction estimated hearing thresholds and (90.8%) of air-bone gaps were within 5 dB, compared to results obtained by conventional audiometry. Thus, threshold differences were not significant. Conclusions: The proposed audiometer is a reliable and valid tool for hearing assessment. Owing to certain limitations, mobile devices can provide a feasible substitute for conventional audiometry in clinical practice.