{"id":155990,"date":"2008-09-01T00:00:00","date_gmt":"2008-09-01T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/automatic-childrens-reading-tutor-on-hand-held-devices\/"},"modified":"2018-10-16T20:12:37","modified_gmt":"2018-10-17T03:12:37","slug":"automatic-childrens-reading-tutor-on-hand-held-devices","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/automatic-childrens-reading-tutor-on-hand-held-devices\/","title":{"rendered":"Automatic Children’s Reading Tutor on Hand-Held Devices"},"content":{"rendered":"

This paper presents an Automatic Reading Tutoring (ART) system using state-of-the-art speech recognition technologies aimed to improve children\u2019s oral reading ability. The features of this system include a compact and robust language model designed for detecting disfluencies in children\u2019s speech, low-footprint implementation, and built-in microphone array. Our system is targeting on hand-held devices to provide better accessibility, flexibility, and freedom for children\u2019s reading practice. The focus of this paper is on the current system\u2019s architecture, which has achieved real-time performance on two hand-held, small-form-factor devices (UMPC and Motion Tablet), with the same detection rate and false alarm rate as on desktop PCs. We also report the latest effort on a prototype system running on a PDA (Windows Mobile 6).<\/p>\n","protected":false},"excerpt":{"rendered":"

This paper presents an Automatic Reading Tutoring (ART) system using state-of-the-art speech recognition technologies aimed to improve children\u2019s oral reading ability. The features of this system include a compact and robust language model designed for detecting disfluencies in children\u2019s speech, low-footprint implementation, and built-in microphone array. Our system is targeting on hand-held devices to provide […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13556,13545,13554],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-155990","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-artificial-intelligence","msr-research-area-human-language-technologies","msr-research-area-human-computer-interaction","msr-locale-en_us"],"msr_publishername":"International Speech Communication Association","msr_edition":"Proceedings of InterSpeech,2008, Proceedings of 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