@inproceedings{bragg2015a,
author = {Bragg, Danielle and Rector, K. and Ladner, R.},
title = {A User-Powered American Sign Language Dictionary},
organization = {ACM SIGACCESS},
booktitle = {Proceedings of the 18th International ACM SIGACCESS Conference on Computers and Accessibility},
year = {2015},
month = {March},
abstract = {Sounds provide informative signals about the world around us. In situations where non-auditory cues are inaccessible, it can be useful for deaf and hard-of-hearing people to be notified about sounds. Through a survey, we explored which sounds are of interest to deaf and hard-of-hearing people, and which means of notification are appropriate. Motivated by these findings, we designed a mobile phone app that alerts deaf and hard-of-hearing people to sounds they care about. The app uses training examples of personally relevant sounds recorded by the user to learn a model of those sounds. It then screens the incoming audio stream from the phone’s microphone for those sounds. When it detects a sound, it alerts the user by vibrating and providing a pop-up notification. To evaluate the interface design independent of sound detection errors, we ran a Wizard-of-Oz user study, and found that the app design successfully facilitated deaf and hard-of-hearing users recording training examples. We also explored the viability of a basic machine learning algorithm for sound detection.},
publisher = {ACM},
url = {http://approjects.co.za/?big=en-us/research/publication/a-user-powered-american-sign-language-dictionary/},
pages = {3-13},
}