{"id":503657,"date":"2018-08-29T09:10:08","date_gmt":"2018-08-29T16:10:08","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=503657"},"modified":"2018-10-16T20:19:39","modified_gmt":"2018-10-17T03:19:39","slug":"personal-data-exploration-with-speech-on-mobile-devices","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/personal-data-exploration-with-speech-on-mobile-devices\/","title":{"rendered":"Personal Data Exploration with Speech on Mobile Devices"},"content":{"rendered":"

In this article, we envision a novel way to help people explore their personal data on mobile devices by leveraging speech interaction. Supporting visual data exploration on mobile devices pertains to two constraints. First, mobile devices\u2019 small screen cannot afford a panel of widgets. Second, exploring self-tracking data often involves entering specific date and time, or their ranges, which is tedious to do on mobile devices. These challenges can be addressed through speech because it does not require much space and is flexible enough to cover different ways to specify date and time. Moreover, common personal insight types identified from prior work allow us to narrow the scope of the speech interaction needed for personal data exploration, making it more tractable with the state-of-the-art speech recognition technology.<\/p>\n","protected":false},"excerpt":{"rendered":"

In this article, we envision a novel way to help people explore their personal data on mobile devices by leveraging speech interaction. Supporting visual data exploration on mobile devices pertains to two constraints. First, mobile devices\u2019 small screen cannot afford a panel of widgets. Second, exploring self-tracking data often involves entering specific date and time, […]<\/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":[13563,13554],"msr-publication-type":[193724],"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-503657","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-data-platform-analytics","msr-research-area-human-computer-interaction","msr-locale-en_us"],"msr_publishername":"","msr_edition":"","msr_affiliation":"","msr_published_date":"2018-05-29","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":"","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":"503660","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","title":"PDEonMobile-MultimodalVis2018","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2018\/08\/PDEonMobile-MultimodalVis2018.pdf","id":503660,"label_id":0}],"msr_related_uploader":"","msr_attachments":[],"msr-author-ordering":[{"type":"guest","value":"eun-kyoung-choe","user_id":365921,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=eun-kyoung-choe"},{"type":"user_nicename","value":"Bongshin Lee","user_id":31276,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Bongshin Lee"},{"type":"text","value":"Seung-won Hwang","user_id":0,"rest_url":false}],"msr_impact_theme":[],"msr_research_lab":[199565],"msr_event":[],"msr_group":[371909,379814],"msr_project":[496430,365810],"publication":[],"video":[],"download":[],"msr_publication_type":"miscellaneous","related_content":{"projects":[{"ID":496430,"post_title":"Data Visualization on Mobile Devices","post_name":"data-visualization-on-mobile-devices","post_type":"msr-project","post_date":"2018-07-20 08:32:58","post_modified":"2022-10-01 16:25:41","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/data-visualization-on-mobile-devices\/","post_excerpt":"What are the mobile-inherent and application-specific challenges in designing interfaces for visualizing and exploring data on mobile devices? How can we address these challenges? What are new and exciting ways to use mobile devices for data visualization?","_links":{"self":[{"href":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/wp\/v2\/msr-project\/496430"}]}},{"ID":365810,"post_title":"Human-Data Interaction for Self-Monitoring","post_name":"human-data-interaction","post_type":"msr-project","post_date":"2017-02-24 09:52:42","post_modified":"2023-02-07 09:16:18","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/human-data-interaction\/","post_excerpt":"Empowering people to improve their lives by fully leveraging the data about themselves   In recent years, we have witnessed rapid advancements in consumer health technologies. People are also increasingly tracking personal health data outside the clinic using wearable sensing devices and mobile health applications. For example, we have observed the rise of the Quantified Self (QS) movement, which aims to improve health, maximize work performance, and find new life experiences through self-tracking. 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