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,"_classifai_error":"","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-post-option":[],"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 Interspeech","msr_affiliation":"","msr_published_date":"2008-09-01","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"1733-1736","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"","msr_how_published":"","msr_notes":"Brisbane, Australia","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":"224998","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","title":"Fianl_is08_inProceeding.pdf","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2008\/09\/Fianl_is08_inProceeding.pdf","id":224998,"label_id":0}],"msr_related_uploader":"","msr_attachments":[{"id":224998,"url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2008\/09\/Fianl_is08_inProceeding.pdf"}],"msr-author-ordering":[{"type":"user_nicename","value":"xiaolli","user_id":34889,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=xiaolli"},{"type":"user_nicename","value":"deng","user_id":31602,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=deng"},{"type":"user_nicename","value":"yuncj","user_id":35068,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=yuncj"},{"type":"user_nicename","value":"alexac","user_id":30932,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=alexac"}],"msr_impact_theme":[],"msr_research_lab":[],"msr_event":[],"msr_group":[],"msr_project":[169434,169630],"publication":[],"video":[],"download":[],"msr_publication_type":"inproceedings","related_content":{"projects":[{"ID":169434,"post_title":"Acoustic Modeling","post_name":"acoustic-modeling","post_type":"msr-project","post_date":"2004-01-29 16:42:42","post_modified":"2019-08-14 14:50:04","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/acoustic-modeling\/","post_excerpt":"Acoustic modeling of speech typically refers to the process of\u00a0establishing statistical\u00a0representations for the feature vector sequences\u00a0computed from the speech waveform. 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