Method of learning character segments from received text, and associated handheld electronic device
View Patent ↗An improved method of learning character segments from received text enables facilitated text input on an improved handheld electronic device. In receiving text on the handheld electronic device, the characters of the text are converted into the inputs with which the characters correspond. Then, segments and other objects are analyzed to generate a proposed character interpretation of the series of inputs. Responsive to detecting that at least a portion of the character interpretation differs from a corresponding portion of the received text, a character learning string comprising the differing characters of the received text are stored as a candidate. In response to receiving additional text on the handheld electronic device, the characters of the additional text are converted into the inputs with which the characters correspond. Then, segments and other objects are analyzed to generate another proposed character interpretation of the series of additional inputs. Responsive to detecting that at least a portion of the another character interpretation differs from a corresponding portion of the additional received text, another character learning string comprising the differing characters of the additional received text are compared with the candidate. If a set of characters in the another character learning string match characters in the candidate, the set of characters are stored as a segment.
1. A method of enabling input on an electronic device having stored therein a plurality of objects that comprise a number of raw inputs, a number of characters, and a number of segments, each raw input having one or more of the characters associated therewith, each segment comprising a plurality of the characters, the method comprising:
receiving a string of reference characters;
obtaining the raw inputs with which the reference characters are associated;
generating a proposed character interpretation of the obtained raw inputs;
determining that at least a portion of the proposed character interpretation and a corresponding at least portion of the string of reference characters differ; and
responsive to the determining, storing the at least portion of the string of reference characters as an object of the plurality of objects.
2. The method of claim 1 wherein the plurality of objects further comprise a number of candidates, and further comprising:
making a determination that no candidate matches the at least portion of the string of reference characters; and
responsive to the making of the determination, storing the at least portion of the string of reference characters as at least a portion of a candidate.
3. The method of claim 1 wherein the plurality of objects further comprise a number of candidates, and further comprising:
making a determination that at least a portion of a particular candidate matches the at least portion of the string of reference characters; and
responsive to the making of the determination, storing the at least portion of the string of reference characters as at least a portion of a segment.
4. The method of claim 3 , further comprising deleting the particular candidate.
5. The method of claim 3 wherein the plurality of objects further comprise a number of combination objects, each combination object comprising a segment plus one of a character and a segment, and further comprising determining that the at least portion of the string of reference characters comprises more than a predetermined quantity of characters and, responsive thereto, storing the at least portion of the string of reference characters as at least a portion of a combination object.
6. The method of claim 1 wherein the plurality of objects further comprise a number of candidates and a number of combination objects, each combination object comprising a segment plus one of a character and a segment, and wherein the number of segments comprise a number of generic segments and a number of learned segments, and further comprising consulting one or more of the number of raw inputs, the number of characters, the number of combination objects, the number of generic segments, the number of learned segments, and the number of candidates in the generating of the proposed character interpretation.
7. An electronic device comprising:
a processor apparatus that comprises a processor and a memory having stored therein a plurality of objects that comprise a number of raw inputs, a number of characters, and a number of segments, each raw input having one or more of the characters associated therewith, each segment comprising a plurality of the characters, the memory further having stored therein a number of routines which, when executed on the processor, cause the electronic device to perform operations comprising:
receiving a string of reference characters;
obtaining the raw inputs with which the reference characters are associated;
generating a proposed character interpretation of the obtained raw inputs;
determining that at least a portion of the proposed character interpretation and a corresponding at least portion of the string of reference characters differ; and
responsive to the determining, storing the at least portion of the string of reference characters as an object of the plurality of objects.
8. The electronic device of claim 7 wherein the plurality of objects further comprise a number of candidates, and wherein the operations further comprise:
making a determination that no candidate matches the at least portion of the string of reference characters; and
responsive to the making of the determination, storing the at least portion of the string of reference characters as at least a portion of a candidate.
9. The electronic device of claim 7 wherein the plurality of objects further comprise a number of candidates, and wherein the operations further comprise:
making a determination that at least a portion of a particular candidate matches the at least portion of the string of reference characters; and
responsive to the making of the determination, storing the at least portion of the string of reference characters as at least a portion of a segment.
10. The electronic device of claim 9 wherein the operations further comprise deleting the particular candidate.
11. The electronic device of claim 9 wherein the plurality of objects further comprise a number of combination objects, each combination object comprising a segment plus one of a character and a segment, and wherein the operations further comprise determining that the at least portion of the string of reference characters comprises more than a predetermined quantity of characters and, responsive thereto, storing the at least portion of the string of reference characters as at least a portion of a combination object.
12. The electronic device of claim 7 wherein the plurality of objects further comprise a number of candidates and a number of combination objects, each combination object comprising a segment plus one of a character and a segment, and wherein the number of segments comprise a number of generic segments and a number of learned segments, and wherein the operations further comprise consulting one or more of the number of raw inputs, the number of characters, the number of combination objects, the number of generic segments, the number of learned segments, and the number of candidates in the generating of the proposed character interpretation.