Literature DB >> 33105267

Auditory Measures for the Next Billion Users.

Malcolm Slaney1, Richard F Lyon, Ricardo Garcia, Brian Kemler, Chet Gnegy, Kevin Wilson, Dimitri Kanevsky, Sagar Savla, Vinton G Cerf.   

Abstract

A range of new technologies have the potential to help people, whether traditionally considered hearing impaired or not. These technologies include more sophisticated personal sound amplification products, as well as real-time speech enhancement and speech recognition. They can improve user's communication abilities, but these new approaches require new ways to describe their success and allow engineers to optimize their properties. Speech recognition systems are often optimized using the word-error rate, but when the results are presented in real time, user interface issues become a lot more important than conventional measures of auditory performance. For example, there is a tradeoff between minimizing recognition time (latency) by quickly displaying results versus disturbing the user's cognitive flow by rewriting the results on the screen when the recognizer later needs to change its decisions. This article describes current, new, and future directions for helping billions of people with their hearing. These new technologies bring auditory assistance to new users, especially to those in areas of the world without access to professional medical expertise. In the short term, audio enhancement technologies in inexpensive mobile forms, devices that are quickly becoming necessary to navigate all aspects of our lives, can bring better audio signals to many people. Alternatively, current speech recognition technology may obviate the need for audio amplification or enhancement at all and could be useful for listeners with normal hearing or with hearing loss. With new and dramatically better technology based on deep neural networks, speech enhancement improves the signal to noise ratio, and audio classifiers can recognize sounds in the user's environment. Both use deep neural networks to improve a user's experiences. Longer term, auditory attention decoding is expected to allow our devices to understand where a user is directing their attention and thus allow our devices to respond better to their needs. In all these cases, the technologies turn the hearing assistance problem on its head, and thus require new ways to measure their performance.

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Year:  2020        PMID: 33105267     DOI: 10.1097/AUD.0000000000000955

Source DB:  PubMed          Journal:  Ear Hear        ISSN: 0196-0202            Impact factor:   3.570


  5 in total

1.  Comparing In-ear EOG for Eye-Movement Estimation With Eye-Tracking: Accuracy, Calibration, and Speech Comprehension.

Authors:  Martin A Skoglund; Martin Andersen; Martha M Shiell; Gitte Keidser; Mike Lind Rank; Sergi Rotger-Griful
Journal:  Front Neurosci       Date:  2022-06-30       Impact factor: 5.152

Review 2.  Harnessing the Power of Artificial Intelligence in Otolaryngology and the Communication Sciences.

Authors:  Blake S Wilson; Debara L Tucci; David A Moses; Edward F Chang; Nancy M Young; Fan-Gang Zeng; Nicholas A Lesica; Andrés M Bur; Hannah Kavookjian; Caroline Mussatto; Joseph Penn; Sara Goodwin; Shannon Kraft; Guanghui Wang; Jonathan M Cohen; Geoffrey S Ginsburg; Geraldine Dawson; Howard W Francis
Journal:  J Assoc Res Otolaryngol       Date:  2022-04-20

3.  Pocketable Labs for Everyone: Synchronized Multi-Sensor Data Streaming and Recording on Smartphones with the Lab Streaming Layer.

Authors:  Sarah Blum; Daniel Hölle; Martin Georg Bleichner; Stefan Debener
Journal:  Sensors (Basel)       Date:  2021-12-05       Impact factor: 3.576

4.  Synchronization of ear-EEG and audio streams in a portable research hearing device.

Authors:  Steffen Dasenbrock; Sarah Blum; Paul Maanen; Stefan Debener; Volker Hohmann; Hendrik Kayser
Journal:  Front Neurosci       Date:  2022-09-01       Impact factor: 5.152

5.  The Quest for Ecological Validity in Hearing Science: What It Is, Why It Matters, and How to Advance It.

Authors:  Gitte Keidser; Graham Naylor; Douglas S Brungart; Andreas Caduff; Jennifer Campos; Simon Carlile; Mark G Carpenter; Giso Grimm; Volker Hohmann; Inga Holube; Stefan Launer; Thomas Lunner; Ravish Mehra; Frances Rapport; Malcolm Slaney; Karolina Smeds
Journal:  Ear Hear       Date:  2020 Nov/Dec       Impact factor: 3.562

  5 in total

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