{"id":"https://openalex.org/W3161388737","doi":"https://doi.org/10.1145/3411764.3445166","title":"PhraseFlow: Designs and Empirical Studies of Phrase-Level Input","display_name":"PhraseFlow: Designs and Empirical Studies of Phrase-Level Input","publication_year":2021,"publication_date":"2021-05-06","ids":{"openalex":"https://openalex.org/W3161388737","doi":"https://doi.org/10.1145/3411764.3445166","mag":"3161388737"},"language":"en","primary_location":{"id":"doi:10.1145/3411764.3445166","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3411764.3445166","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3411764.3445166","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3411764.3445166","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5056312119","display_name":"Mingrui Ray Zhang","orcid":null},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Mingrui Ray Zhang","raw_affiliation_strings":["The Information School University of Washington, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The Information School University of Washington, United States","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005293560","display_name":"Shumin Zhai","orcid":"https://orcid.org/0000-0003-0752-2090"},"institutions":[{"id":"https://openalex.org/I1291425158","display_name":"Google (United States)","ror":"https://ror.org/00njsd438","country_code":"US","type":"company","lineage":["https://openalex.org/I1291425158","https://openalex.org/I4210128969"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Shumin Zhai","raw_affiliation_strings":["Google, United States"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Google, United States","institution_ids":["https://openalex.org/I1291425158"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":4.5509,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.95159273,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"13"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12607","display_name":"Personal Information Management and User Behavior","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12607","display_name":"Personal Information Management and User Behavior","score":0.9993000030517578,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10789","display_name":"Interactive and Immersive Displays","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10470","display_name":"Usability and User Interface Design","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/phrase","display_name":"Phrase","score":0.9482837915420532},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7847267389297485},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5197862386703491},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.4874134361743927},{"id":"https://openalex.org/keywords/word-error-rate","display_name":"Word error rate","score":0.4468463957309723},{"id":"https://openalex.org/keywords/empirical-research","display_name":"Empirical research","score":0.4404955804347992},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.43808358907699585},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.4175848066806793},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.405942440032959},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.33618780970573425},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.32787400484085083},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.1388193964958191},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.08001047372817993},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.0778561532497406},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.06606769561767578}],"concepts":[{"id":"https://openalex.org/C2776224158","wikidata":"https://www.wikidata.org/wiki/Q187931","display_name":"Phrase","level":2,"score":0.9482837915420532},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7847267389297485},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5197862386703491},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.4874134361743927},{"id":"https://openalex.org/C40969351","wikidata":"https://www.wikidata.org/wiki/Q3516228","display_name":"Word error rate","level":2,"score":0.4468463957309723},{"id":"https://openalex.org/C120936955","wikidata":"https://www.wikidata.org/wiki/Q2155640","display_name":"Empirical research","level":2,"score":0.4404955804347992},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.43808358907699585},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.4175848066806793},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.405942440032959},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.33618780970573425},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.32787400484085083},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.1388193964958191},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.08001047372817993},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0778561532497406},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.06606769561767578},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3411764.3445166","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3411764.3445166","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3411764.3445166","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3411764.3445166","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3411764.3445166","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3411764.3445166","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3161388737.pdf","grobid_xml":"https://content.openalex.org/works/W3161388737.grobid-xml"},"referenced_works_count":43,"referenced_works":["https://openalex.org/W1557496348","https://openalex.org/W1647671624","https://openalex.org/W1984314602","https://openalex.org/W1984520644","https://openalex.org/W1995987545","https://openalex.org/W2001340812","https://openalex.org/W2001590643","https://openalex.org/W2010645028","https://openalex.org/W2034225924","https://openalex.org/W2051780479","https://openalex.org/W2054689358","https://openalex.org/W2058049219","https://openalex.org/W2069657084","https://openalex.org/W2077940530","https://openalex.org/W2098924240","https://openalex.org/W2099287431","https://openalex.org/W2118711147","https://openalex.org/W2118966134","https://openalex.org/W2130736456","https://openalex.org/W2133990837","https://openalex.org/W2134237567","https://openalex.org/W2140327016","https://openalex.org/W2148723390","https://openalex.org/W2157289187","https://openalex.org/W2207077738","https://openalex.org/W2401452835","https://openalex.org/W2539241874","https://openalex.org/W2583431183","https://openalex.org/W2605133364","https://openalex.org/W2605710880","https://openalex.org/W2795386701","https://openalex.org/W2795433822","https://openalex.org/W2796141725","https://openalex.org/W2916904544","https://openalex.org/W2941463876","https://openalex.org/W2942331292","https://openalex.org/W2942986209","https://openalex.org/W2947160092","https://openalex.org/W2978284326","https://openalex.org/W2981305380","https://openalex.org/W4206205808","https://openalex.org/W4245593659","https://openalex.org/W6646387163"],"related_works":["https://openalex.org/W2039546652","https://openalex.org/W2012262991","https://openalex.org/W2373794620","https://openalex.org/W3203142394","https://openalex.org/W2357294589","https://openalex.org/W2386861027","https://openalex.org/W2060629350","https://openalex.org/W2349302580","https://openalex.org/W4302615923","https://openalex.org/W2944691285"],"abstract_inverted_index":{"Decoding":[0],"on":[1,9,52],"phrase-level":[2,17,41,61,75,145],"may":[3],"afford":[4],"more":[5],"correction":[6],"accuracy":[7],"than":[8],"word-level":[10],"according":[11],"to":[12,26,30,47,81,142],"previous":[13,49],"research.":[14],"However,":[15],"how":[16,25],"input":[18,42,55,62,76,146],"affects":[19],"the":[20,28,53,64,82,95,101,138,144],"user":[21,83],"typing":[22],"behavior,":[23],"and":[24],"design":[27,96],"interaction":[29],"make":[31],"it":[32],"practical":[33],"remain":[34],"under":[35],"explored.":[36],"We":[37,72],"present":[38],"PhraseFlow,":[39],"a":[40,127],"keyboard":[43],"that":[44,60,74,84,99,108,135],"is":[45],"able":[46],"correct":[48],"text":[50],"based":[51],"subsequently":[54],"sequences.":[56],"Computational":[57],"studies":[58],"show":[59],"reduces":[63],"error":[65,118],"rate":[66],"of":[67,97,137],"autocorrection":[68],"by":[69],"over":[70],"16%.":[71],"found":[73],"introduced":[77],"extra":[78],"cognitive":[79,102],"load":[80],"hindered":[85],"their":[86],"performance.":[87],"Through":[88],"an":[89],"iterative":[90],"design-implement-research":[91],"process,":[92],"we":[93,125],"optimized":[94],"PhraseFlow":[98,112],"alleviated":[100],"load.":[103],"An":[104],"in-lab":[105],"study":[106,130],"shows":[107],"users":[109,139],"could":[110],"adopt":[111],"quickly,":[113],"resulting":[114],"in":[115,148],"19%":[116],"fewer":[117],"without":[119],"losing":[120],"speed.":[121],"In":[122],"real-life":[123],"settings,":[124],"conducted":[126],"six-day":[128],"deployment":[129],"with":[131],"42":[132],"participants,":[133],"showing":[134],"78.6%":[136],"would":[140],"like":[141],"have":[143],"feature":[147],"future":[149],"keyboards.":[150]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":5}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}