{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T15:54:14Z","timestamp":1782834854732,"version":"3.54.5"},"reference-count":19,"publisher":"Association for Computing Machinery (ACM)","issue":"MHCI","license":[{"start":{"date-parts":[[2022,9,19]],"date-time":"2022-09-19T00:00:00Z","timestamp":1663545600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["Proc. ACM Hum.-Comput. Interact."],"published-print":{"date-parts":[[2022,9,19]]},"abstract":"<jats:p>We introduce a framework for adapting a virtual keyboard to individual user behavior by modifying a Gaussian spatial model to use personalized key center offset means and, optionally, learned covariances. Through numerous real-world studies, we determine the importance of training data quantity and weights, as well as the number of clusters into which to group keys to avoid overfitting. While past research has shown potential of this technique using artificially-simple virtual keyboards and games or fixed typing prompts, we demonstrate effectiveness using the highly-tuned Gboard app with a representative set of users and their real typing behaviors. Across a variety of top languages, we achieve small-but-significant improvements in both typing speed and decoder accuracy.<\/jats:p>","DOI":"10.1145\/3546737","type":"journal-article","created":{"date-parts":[[2022,9,20]],"date-time":"2022-09-20T23:14:30Z","timestamp":1663715670000},"page":"1-17","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":4,"title":["Spatial Model Personalization in Gboard"],"prefix":"10.1145","volume":"6","author":[{"given":"Gary","family":"Sivek","sequence":"first","affiliation":[{"name":"Google LLC, New York, NY, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael","family":"Riley","sequence":"additional","affiliation":[{"name":"Google LLC, New York, NY, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2022,9,20]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/2371574.2371612"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/2166966.2166969"},{"key":"e_1_2_1_3_1","volume-title":"Classification and regression trees","author":"Breiman Leo","unstructured":"Leo Breiman , Jerome Friedman , Charles J Stone , and Richard A Olshen . 1984. Classification and regression trees . CRC press . Leo Breiman, Jerome Friedman, Charles J Stone, and Richard A Olshen. 1984. Classification and regression trees. CRC press."},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1145\/3173574.3173829"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/3173574.3174220"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/2207676.2208662"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/2470654.2481386"},{"key":"e_1_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1145\/2207676.2208658"},{"key":"e_1_2_1_9_1","volume-title":"Statistical methods for speech recognition","author":"Jelinek Frederick","unstructured":"Frederick Jelinek . 1998. Statistical methods for speech recognition . MIT press . Frederick Jelinek. 1998. Statistical methods for speech recognition. MIT press."},{"key":"e_1_2_1_10_1","volume-title":"Machine learning: a probabilistic perspective","author":"Murphy Kevin P","unstructured":"Kevin P Murphy . 2012. Machine learning: a probabilistic perspective . MIT press . Kevin P Murphy. 2012. Machine learning: a probabilistic perspective. MIT press."},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1080\/07370024.2015.1071195"},{"key":"e_1_2_1_12_1","volume-title":"Francc oise Beaufays, and Michael Riley","author":"Ouyang Tom","year":"2017","unstructured":"Tom Ouyang , David Rybach , Francc oise Beaufays, and Michael Riley . 2017 . Mobile keyboard input decoding with finite-state transducers. arXiv preprint arXiv:1704.03987 (2017). Tom Ouyang, David Rybach, Francc oise Beaufays, and Michael Riley. 2017. Mobile keyboard input decoding with finite-state transducers. arXiv preprint arXiv:1704.03987 (2017)."},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/3338286.3340120"},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1080\/07370024.2016.1215922"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/2702123.2702597"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1145\/1835804.1835810"},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1145\/2380116.2380175"},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/2330667.2330689"},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/3173574.3174013"}],"container-title":["Proceedings of the ACM on Human-Computer Interaction"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3546737","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3546737","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T18:44:04Z","timestamp":1750272244000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3546737"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,9,19]]},"references-count":19,"journal-issue":{"issue":"MHCI","published-print":{"date-parts":[[2022,9,19]]}},"alternative-id":["10.1145\/3546737"],"URL":"https:\/\/doi.org\/10.1145\/3546737","relation":{},"ISSN":["2573-0142"],"issn-type":[{"value":"2573-0142","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,9,19]]},"assertion":[{"value":"2022-09-20","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}