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Comput."],"published-print":{"date-parts":[[2024,9,30]]},"abstract":"<jats:p>\n            People learning American Sign Language (ASL) and practicing their comprehension skills will often encounter complex ASL videos that may contain unfamiliar signs. Existing dictionary tools require users to isolate a single unknown sign before initiating a search by selecting linguistic properties or performing the sign in front of a webcam. This process presents challenges in extracting and reproducing unfamiliar signs, disrupting the video-watching experience, and requiring learners to rely on external dictionaries. We explore a technology that allows users to select and view dictionary results for one or more unfamiliar signs while watching a video. We interviewed 14 ASL learners to understand their challenges in understanding ASL videos, strategies for dealing with unfamiliar vocabulary, and expectations for an\n            <jats:italic>in situ<\/jats:italic>\n            dictionary system. We then conducted an in-depth analysis with eight learners to examine their interactions with a Wizard-of-Oz prototype during a video comprehension task. Finally, we conducted a comparative study with six additional ASL learners to evaluate the speed, accuracy, and workload benefits of an embedded dictionary-search feature within a video player. Our tool outperformed a baseline in the form of an existing online dictionary across all three metrics. The integration of a search tool and span selection offered advantages for video comprehension. Our findings have implications for designers, computer vision researchers, and sign language educators.\n          <\/jats:p>","DOI":"10.1145\/3690647","type":"journal-article","created":{"date-parts":[[2024,9,2]],"date-time":"2024-09-02T12:54:40Z","timestamp":1725281680000},"page":"1-35","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":2,"title":["Exploring the Benefits and Applications of Video-Span Selection and Search for Real-Time Support in Sign Language Video Comprehension among ASL Learners"],"prefix":"10.1145","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2792-2964","authenticated-orcid":false,"given":"Saad","family":"Hassan","sequence":"first","affiliation":[{"name":"Tulane University, New Orleans, LA, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5046-9884","authenticated-orcid":false,"given":"Calu\u00e3","family":"de Lacerda Pataca","sequence":"additional","affiliation":[{"name":"Computing and Information Science, Rochester Institute of Technology, Rochester, NY, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0072-743X","authenticated-orcid":false,"given":"Akhter Al","family":"Amin","sequence":"additional","affiliation":[{"name":"Computing and Information Science, Rochester Institute of Technology, Rochester, NY, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5214-794X","authenticated-orcid":false,"given":"Laleh","family":"Nourian","sequence":"additional","affiliation":[{"name":"Computing and Information Science, Rochester Institute of Technology, Rochester, NY, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-1296-2141","authenticated-orcid":false,"given":"Diego","family":"Navarro","sequence":"additional","affiliation":[{"name":"National Institute for the Deaf, Rochester Institute of Technology, Rochester, NY, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4971-2004","authenticated-orcid":false,"given":"Sooyeon","family":"Lee","sequence":"additional","affiliation":[{"name":"New Jersey Institute of Technology, Newark, NJ, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0000-7924-8778","authenticated-orcid":false,"given":"Alexis","family":"Gordon","sequence":"additional","affiliation":[{"name":"School of Information, Rochester Institute of Technology, Rochester, NY, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3133-8664","authenticated-orcid":false,"given":"Matthew","family":"Watkins","sequence":"additional","affiliation":[{"name":"School of Information, Rochester Institute of Technology, Rochester, NY, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3123-6361","authenticated-orcid":false,"given":"Garreth W.","family":"Tigwell","sequence":"additional","affiliation":[{"name":"School of Information, Rochester Institute of Technology, Rochester, NY, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6290-2681","authenticated-orcid":false,"given":"Matt","family":"Huenerfauth","sequence":"additional","affiliation":[{"name":"School of Information, Rochester Institute of Technology, Rochester, NY, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2024,10,4]]},"reference":[{"issue":"2","key":"e_1_3_3_2_2","first-page":"613","article-title":"Sign language translation using deep convolutional neural networks","volume":"14","author":"Abiyev Rahib H.","year":"2020","unstructured":"Rahib H. 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