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 noti\ufb01ed about sounds. Through a survey, we explored which sounds are of interest to deaf and hard-of-hearing people, and which means of noti\ufb01cation are appropriate. Motivated by these \ufb01ndings, 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\u2019s microphone for those sounds. When it detects a sound, it alerts the user by vibrating and providing a pop-up noti\ufb01cation. 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.<\/p>\n","protected":false},"excerpt":{"rendered":"
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 noti\ufb01ed about sounds. Through a survey, we explored which sounds are of interest to deaf and hard-of-hearing people, and which means of noti\ufb01cation are appropriate. Motivated by these […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13554],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-614307","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-human-computer-interaction","msr-locale-en_us"],"msr_publishername":"ACM","msr_edition":"","msr_affiliation":"","msr_published_date":"2015-3-14","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"ACM SIGACCESS","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"url","viewUrl":"false","id":"false","title":"https:\/\/danibragg.com\/papers\/A_User-Powered_American_Sign_Language_Dictionary.pdf","label_id":"243132","label":0},{"type":"doi","viewUrl":"false","id":"false","title":"10.1145\/2675133.2675226","label_id":"243109","label":0}],"msr_related_uploader":"","msr_attachments":[],"msr-author-ordering":[{"type":"user_nicename","value":"Danielle Bragg","user_id":37592,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Danielle Bragg"},{"type":"text","value":"K. Rector","user_id":0,"rest_url":false},{"type":"text","value":"R. Ladner","user_id":0,"rest_url":false}],"msr_impact_theme":[],"msr_research_lab":[199563],"msr_event":[],"msr_group":[],"msr_project":[614286],"publication":[],"video":[],"download":[],"msr_publication_type":"inproceedings","related_content":{"projects":[{"ID":614286,"post_title":"Data-Driven Accessibility Systems","post_name":"data-driven-accessibility-systems","post_type":"msr-project","post_date":"2019-10-28 09:08:40","post_modified":"2023-11-14 18:22:49","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/data-driven-accessibility-systems\/","post_excerpt":"Microsoft Research New England aims to build the accessibility systems of the future. In particular, we are focused on building systems to better support sign language users and low-vision readers. Accessibility is a major concern for many people with disabilities. 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