{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/46525"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/46525","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"A speech-enabled system for website bookmarking","abstract":"In recent years, much advancement has been made in both search and speech technology. The former seeks to organize and retrieve the ever-growing amount of online information efficiently, while the latter strives to increase mobility and accessibility in multimodal devices. Naturally, searching via spoken language will become ubiquitous in the near future. As a step towards realizing this goal, this thesis focuses on the simpler problem of bookmarking and retrieving websites via speech. With data collected from a user study, we gained insight on how to predict speech tags and query utterances based on a webpage's content. We then investigate and evaluate several heuristics for tagging and retrieving bookmarks with the objectives of maximizing recognition accuracy and retrieval rates. Finally, the progress culminates in a prototype Firefox extension that encapsulates an end-to-end system demonstrating speech integration into the bookmarking capabilities of the Firefox browser.","abstract_html":"In recent years, much advancement has been made in both search and speech technology. The former seeks to organize and retrieve the ever-growing amount of online information efficiently, while the latter strives to increase mobility and accessibility in multimodal devices. Naturally, searching via spoken language will become ubiquitous in the near future. As a step towards realizing this goal, this thesis focuses on the simpler problem of bookmarking and retrieving websites via speech. With data collected from a user study, we gained insight on how to predict speech tags and query utterances based on a webpage's content. We then investigate and evaluate several heuristics for tagging and retrieving bookmarks with the objectives of maximizing recognition accuracy and retrieval rates. Finally, the progress culminates in a prototype Firefox extension that encapsulates an end-to-end system demonstrating speech integration into the bookmarking capabilities of the Firefox browser.","abstract_has_math":false,"creators":["Sun, Xin, M. Eng. Massachusetts Institute of Technology"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.","school":null,"contributors":[],"advisors":["James R. Glass."],"committee_chairs":[],"committee_members":[],"year":2008,"date_issued":"2008","date_published":"2008","updated_at":"2026-07-22T22:20:49Z","subjects":["Electrical Engineering and Computer Science."],"languages":["eng"],"rights":["M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission."],"rights_urls":["http://dspace.mit.edu/handle/1721.1/7582"],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1721.1/46525","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["James R. Glass."]},{"key":"dc:contributor.department","label":"Department","values":["Massachusetts Institute of Technology. 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The former seeks to organize and retrieve the ever-growing amount of online information efficiently, while the latter strives to increase mobility and accessibility in multimodal devices. Naturally, searching via spoken language will become ubiquitous in the near future. As a step towards realizing this goal, this thesis focuses on the simpler problem of bookmarking and retrieving websites via speech. With data collected from a user study, we gained insight on how to predict speech tags and query utterances based on a webpage's content. We then investigate and evaluate several heuristics for tagging and retrieving bookmarks with the objectives of maximizing recognition accuracy and retrieval rates. Finally, the progress culminates in a prototype Firefox extension that encapsulates an end-to-end system demonstrating speech integration into the bookmarking capabilities of the Firefox browser."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["M.Eng."]},{"key":"dc:title","label":"Title","values":["A speech-enabled system for website bookmarking"]}]}],"canonical_facts":{"dc:contributor.advisor":["James R. Glass."],"dc:contributor.department":["Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science."],"dc:contributor.other":["Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science."],"dc:creator":["Sun, Xin, M. Eng. Massachusetts Institute of Technology"],"dc:date.accessioned":["2009-08-26T16:42:18Z"],"dc:date.available":["2009-08-26T16:42:18Z"],"dc:date.issued":["2008"],"dc:description":["Thesis (M. 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