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|HAO WAKAT I AKITUS009785630B2 EL DIA DE LINHA MITTE (12 ) United States Patent ( 10 ) Patent No. : US 9 , 785 ,630 B2 Willmore et al . (45 ) Date of Patent: Oct . 10, 2017 ( 54 ) TEXT PREDICTION USING COMBINED ( 56 ) References Cited WORD N -GRAM AND UNIGRAM LANGUAGE MODELS U . S . PATENT DOCUMENTS 1 ,559 ,320 A 10 / 1925 Hirsh ( 71 ) Applicant: Apple Inc ., Cupertino , CA (US ) 2 , 180 ,522 A 11/ 1939 Henne (72 ) Inventors : Christopher P . Willmore , Santa Clara , (Continued ) CA (US ) ; Nicholas K . Jong, Seattle , FOREIGN PATENT DOCUMENTS WA (US ) ; Justin S . Hogg , San Francisco , CA (US ) CA 2666438 C 6 /2013 CH 681573 A5 4 / 1993 (73 ) Assignee : Apple Inc ., Cupertino , CA (US ) ( Continued ) ( * ) Notice : Subject to any disclaimer , the term of this OTHER PUBLICATIONS patent is extended or adjusted under 35 Carpendale et al. , “ 3 -Dimensional Pliable Surfaces: For the Effec U . S . C . 154 (b ) by 2 days. tive Presentation of Visual Information ” , UIST ' 95 Proceedings of the 8th Annual ACM Symposium on User Interface and Software (21 ) Appl . No. : 14/ 724, 641 Technology, Nov. 14 - 17 , 1995 , pp . 217 - 226 . May 28 , 2015 (Continued ) (22 ) Filed : Primary Examiner — Anne Thomas -Homescu (74 ) Attorney , Agent, or Firm — Morrison & Foerster (65 ) Prior Publication Data LLP US 2015 /0347383 A1 Dec . 3 , 2015 (57 ) ABSTRACT Systems and processes are disclosed for predicting words in a text entry environment. Candidate words and probabilities Related U . S . Application Data associated therewith can be determined by combining a (60 ) Provisional application No .62 /005 , 942 , filed on May word n - gram language model and a unigram language 30 , 2014 . model. Using the word n - gram language model , based on previously entered words, candidate words can be identified and a probability can be calculated for each candidate word . (51 ) Int . Ci. Using the unigram language model, based on a character G06F 17 / 20 ( 2006 . 01 ) entered for a new word , candidate words beginning with the G06F 17 /28 ( 2006 .01 ) character can be identified along with a probability for each ( Continued ) candidate word . In some examples , a geometry score can be (52 ) U . S. Ci. included in the unigram probability related to typing geom CPC .. .. G06F 17 /276 ( 2013 . 01 ) etry on a virtual keyboard . The probabilities of the n - gram (58 ) Field of Classification Search language model and unigram model can be combined , and CPC .. GO6F 3 /04886 ; GO6F 3 /0485 ; GO6F 3 /0237 ; the candidate word or words having the highest probability G06F 3 /01 : G06F 9 /4443 : can be displayed for a user. ( Continued ) 20 Claims , 5 Drawing Sheets Process 200 Receive typed input from a user Using a word n - gram model, determine a first probability of a predicted word based on anL 2204 14 a previously entered word Using a unigram model, determine a second probability of the predicted word based on a inom 206 prefix character of a new word Determine a combined probability of the predicted word based on the first probability Consom 208 and the second probability Cause the predicted word to be displayed . 210 based on the combined probability US 9 ,785 , 630 B2 Page 2 (51 ) Int. CI. 4 ,677 , 570 A 6 / 1987 Taki GIOL 15 /00 ( 2013 .01 ) 4 ,680 ,429 A 7 / 1987 Murdock et al. 4 ,680 , 805 A 7 / 1987 Scott GIOL 15 / 04 ( 2013 .01 ) 4 ,686 , 522 A 8 /1987 Hernandez et al . GIOL 15 /06 ( 2013 .01 ) 4 ,688 , 195 A 8 / 1987 Thompson et al. GIOL 15 / 14 ( 2006 . 01 ) 4 ,692 , 941 A 9 / 1987 Jacks et al. 4 ,698 ,625 A 10 / 1987 McCaskill et al. 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