One-row keyboard and approximate typing

Abstract

In one aspect, the present invention comprises an apparatus for character entry on an electronic device, comprising: a keyboard with one row of keys; and an electronic display device in communication with the keyboard; wherein one or more keys on the keyboard has a correspondence with a plurality of characters, and wherein the correspondence enables QWERTY-based typing. In another aspect, the invention comprises an apparatus for character entry on an electronic device, comprising: a keyboard with a plurality of keys; and an electronic display device in communication with the keyboard; wherein one or more keys on the keyboard has a correspondence with a plurality of characters, and wherein, for each of the one or more keys, the plurality of characters comprises: (a) a home row character associated with a particular finger when touch typing; and (b) a non-home-row character associated with the particular finger when touch typing.

1 . A method for reducing predictive uncertainty in a disambiguation group, comprising:
 (i) receiving and storing a computer readable medium a disambiguation group comprising two or more objects, each of said objects associated with one or more object equivalence classes and a legal combination of characters supported by a reduced keyboard;   (ii) receiving and storing in a computer readable medium one or more rules defining legal object equivalence classes or relationships between object equivalence classes;   (iii) predicting at least one object from said disambiguation group based on said object equivalence class association of each of said disambiguation group objects and said one or more rules defining legal object equivalence classes or relationships between object equivalence classes; and   (iv) outputting said at least one predicted object from said disambiguation group.   
     
     
         2 . The method of  claim 1 , wherein each of said objects is further associated with a legal character combination and a length of said legal character combination is (a) greater than some minimum value greater than one, or (b) is delimiter-terminated. 
     
     
         3 . The method of  claim 2 , wherein said legal character combinations comprise only delimiter-terminated character combinations. 
     
     
         4 . The method of  claim 1 , wherein said disambiguation group is determined by the steps of:
 (v) receiving a signature for each key selected by a user of a reduced keyboard, each keysignature pair of said reduced keyboard being unique, each signature associated with at least one dual signature and at least one signature associated with one or more dual signatures, each signature-dual signature pair associated with a unique character supported by said reduced keyboard;   (vi) storing in a computer readable memory a plurality of objects, each of said objects comprising:
 (a) a unique sequence of signature-dual signature pairs derived from at least one set of legal character combinations; and 
 (b) one or more attributes associated with said sequence; 
   (vii) predicting at least one approximate signature sequence based on a sequence of signatures consecutively received from said reduced keyboard;   (viii) for each said approximate signature sequence predicting at least one of said plurality of objects based on said approximate signature sequence and on said object attributes, terminating each such approximate signature sequence when said approximate signature sequence terminates with a signature predicted as a delimiter; and   (ix) outputting at least one of said predicted plurality of objects as a disambiguation group.   
     
     
         5 . The method of  claim 1 , wherein said disambiguation group is determined by a reduced keyboard disambiguation method. 
     
     
         6 . The method of  claim 5 , wherein said reduced keyboard disambiguation method comprises:
 (v) receiving a signature for each key selected by a user of a reduced keyboard, each keysignature pair of said reduced keyboard being unique, each signature associated with at least one dual signature and at least one of said signatures associated with two or more dual signatures, each signature-dual signature pair uniquely associated with a character supported by said reduced keyboard;   (vi) storing in a computer readable memory a plurality of objects, each of said objects comprising:
 (a) a unique sequence of signature-dual signature pairs derived from at least one set of legal beginning-of-word (BOW) character combinations; and 
 (b) one or more attributes associated with said sequence; 
   (vii) for each received signature, predicting at least one of said plurality of objects based on a sequence of said signatures, including said received signature, consecutively received from said reduced keyboard and on said object attributes; each such sequence terminating with a signature predicted as a delimiter; and   (viii) outputting at least one of said predicted plurality of objects as a disambiguation group.   
     
     
         7 . The method of  claim 1 , wherein said rules include rules based on commonly shared object equivalence classes. 
     
     
         8 . The method of  claim 7 , wherein at least one of said commonly shared object equivalence classes defines membership in a common dictionary. 
     
     
         9 . The method of  claim 8 , wherein said common dictionary is a BOW dictionary. 
     
     
         10 . The method of  claim 7 , wherein said commonly shared object equivalence class defines specific functions or operations. 
     
     
         11 . The method of  claim 7 , wherein at least one of said commonly shared object equivalence classes defines specific styles. 
     
     
         12 . The method of  claim 1 , further comprising:
 (v) receiving and storing in a computer readable medium one or more delimiterterminated objects, each of said delimiter-terminated objects being associated with user inputs received prior to or subsequent to inputs associated with said disambiguation group, and each of said delimiter-terminated objects associated with one or more object equivalence classes; and   (vi) predicting at least one object from said disambiguation group based, at least in part, on said equivalence classes of said received delimiter-terminated objects.   
     
     
         13 . The method of  claim 12 , further comprising applying rules defining legal combinations of object-object equivalence pairs. 
     
     
         14 . The method of  claim 13 , wherein said rules are based, at least in part, on rules of Natural Language Processing. 
     
     
         15 . The method of  claim 14 , wherein said Natural Language Processing is based on grammar rules. 
     
     
         16 . The method of  claim 15 , wherein said grammar rules comprise rules relating to parts-of-speech. 
     
     
         17 . The method of  claim 13 , wherein said rules are based on probabilistic inference of terminating object-object equivalence class pairs in legal combinations of object-object equivalence class pairs. 
     
     
         18 . The method of  claim 17 , wherein said probabilistic inference is learned from a fixed source. 
     
     
         19 . The method of  claim 17 , wherein said probabilistic inference is learned on-the-fly based on user input. 
     
     
         20 . The method of  claim 17 , wherein said rules admit said object-object equivalence pairs within said disambiguation group only with a probabilistic inference exceeding some minimum value greater than zero. 
     
     
         21 . The method of  claim 17 , wherein said rules admit said object-object equivalence pairs within said disambiguation group only with a probabilistic inference greater than the frequency-of-use of the object with the greatest frequency-of-use in the disambiguation group. 
     
     
         22 . The method of  claim 17 , wherein each of said objects in said disambiguation group is further associated with a frequency-of-use. 
     
     
         23 . The method of  claim 22 , wherein said frequency-of-use is path frequency. 
     
     
         24 . The method of  claim 22 , wherein said prediction is based, at least in part, on selecting an object in said disambiguation group with a greater of either frequency-of-use or probabilistic inference. 
     
     
         25 . The method of  claim 12 , wherein in said step of receiving and storing in a computer readable medium one or more delimiter-terminated objects, each of said delimiterterminated objects is only associated with user inputs received prior to, and not subsequent to, inputs associated with said disambiguation group. 
     
     
         26 . The method of  claim 25 , wherein at least one of said delimiter-terminated objects is a delimiter-terminated object associated with user input received just prior to inputs associated with said disambiguation group. 
     
     
         27 . The method of  claim 25 , wherein said delimiter-terminated objects comprise two delimiter-terminated objects associated with user input received just prior to inputs associated with said disambiguation group. 
     
     
         28 . The method of  claim 1 , wherein said object equivalence classes are generated by aggregating more than one object equivalence class from a first set of object equivalence classes into a new object equivalence class. 
     
     
         29 . A method for selecting a character combination in a disambiguation group for output to a user comprising:
 (i) receiving a disambiguation group of two or more objects, each of said objects associated with a legal combination of characters supported by a reduced keyboard;   (ii) implementing a display algorithm that selects one object in said disambiguation group based on one or more quantifications of user experience;   (iii) outputting a character combination associated with said selected object for display to said user.   
     
     
         30 . The method of  claim 29 , wherein at least one of said one or more quantifications of user experience is based, at least in part, on minimizing one or more cost functions. 
     
     
         31 . The method of  claim 30 , wherein said objects are further associated with a frequency-of-use. 
     
     
         32 . The method of  claim 31 , wherein minimizing cost if based on (a) minimizing average cost associated with said one or more cost functions, (b) said character combinations, and (c) said frequency-of-use associated with each of said objects. 
     
     
         33 . The method of  claim 30 , wherein at least one cost function is based on a differential or incremental cost function. 
     
     
         34 . The method of  claim 30 , wherein cost associated with at least one cost function is based, at least in part, on a number of characters associated with said objects in said disambiguation group. 
     
     
         35 . The method of  claim 29 , wherein said display algorithm is based on, at least in part, a beginning of word path ordering (BOW/po). 
     
     
         36 . The method of  claim 29 , wherein said display algorithm is based on, at least in part, minimizing number of changes to a character combination currently displayed to said user. 
     
     
         37 . The method of  claim 29 , further comprising:
 (iv) receiving a signal from said reduced keyboard indicating that the user has rejected said character combination associated with said selected object;   (v) modifying said disambiguation group by eliminating said object associated with said rejected character combination;   (vi) modifying said on or more quantifications of user experience based on said eliminated object and selecting one object from said modified disambiguation group based on said modified one or more quantifications of user experience;   (vii) outputting said character combination associated with said selected object for display to said user.