Handwriting and voice input with automatic correction

• US 20050192802A1
• Filed: 01/25/2005
• Published: 09/01/2005
• Est. Priority Date: 02/11/2004
• Status: Abandoned Application

• Current Assignee: Tegic Communications, Inc. (Microsoft Corporation)
• Original Assignee: Tegic Communications, Inc. (Microsoft Corporation)
• Inventors: Kay, David, Robinson, Alex, Meurs, Pim Van, Bradford, Ethan, Stephanick, James
• Application Number:
  US11/043,525
• Publication Number:
  US 20050192802A1
• Time in Patent Office: Days
• US Class Current: 704/240
• CPC Class Codes: G06V 30/10 Character recognition
• CPC Class Codes: G06V 30/2272 with lexical matching
• CPC Class Codes: G06V 30/268 Lexical context
• CPC Class Codes: G06V 30/274 Syntactic or semantic context, e.g. balancing
• CPC Class Codes: G10L 15/18 using natural language modelling

Abstract

A hybrid approach to improve handwriting recognition and voice recognition in data process systems is disclosed. In one embodiment, a front end is used to recognize strokes, characters and/or phonemes. The front end returns candidates with relative or absolute probabilities of matching to the input. Based on linguistic characteristics of the language, e.g. alphabetical or ideographic language for the words being entered, e.g. frequency of words and phrases being used, likely part of speech of the word entered, the morphology of the language, or the context in which the word is entered), a back end combines the candidates determined by the front end from inputs for words to match with known words and the probabilities of the use of such words in the current context.

Claims

1. A method for recognizing language input in a data processing system, comprising the steps of:

processing a user input of a word of a language through pattern recognition to generate a plurality of recognition results for a plurality of word components, respectively, at least one of the plurality of recognition results comprising a plurality of word component candidates and a plurality of probability indicators, the plurality of probability indicators indicating degrees of probability of matching of the plurality of word components to a portion of the user input relative to each other; and

determining one or more word candidates for the user input of the word from the plurality of recognition results and from data indicating probability of usage of a list of words.

2. The method of claim 1, wherein the pattern recognition comprises handwriting recognition.

3. The method of claim 2, wherein each of the plurality of word component candidates comprises a stroke;

and the word comprises an ideographic language symbol.

4. The method of claim 2, wherein each of the plurality of word component candidates comprises a character;

and the word comprises an alphabetical word.

5. The method of claim 1, wherein the pattern recognition comprises speech recognition;

and each of the plurality of word component candidates comprises a phoneme.

6. The method of claim 1, wherein one of the plurality of recognition results for a word component comprises an indication that any one of a set of word component candidates has an equal probability of matching a portion of the user input for the word;

and the set of word component candidates comprises alphabetic characters of the language.

7. The method of claim 1, wherein the data indicating probability of usage of the list of words comprises any of:

frequencies of word usages in the language;

frequencies of word usages by a user; and

frequencies of word usages in a document.

8. The method of claim 1, wherein the data indicating probability of usage of the list of words comprises any of:

phrases in the language;

word pairs in the language; and

word trigrams in the language.

9. The method of claim 1, wherein the data indicating probability of usage of the list of words comprises any of:

data representing morphology of the language; and

data representing grammatical rules of the language.

10. The method of claim 1, wherein the data indicating probability of usage of the list of words comprises:

data representing a context in which the user input of the word is received.

11. The method of claim 1, wherein the user input specifies only a portion of a complete set of word components for the word.

12. The method of claim 1, wherein the one or more word candidates comprise a portion of words formed from combinations of word component candidates in the plurality of recognition results and a portion of words containing combinations of word component candidates in the plurality of recognition results.

13. The method of claim 1, wherein the one or more word candidates comprise a plurality of word candidates;

and the method further comprises the steps of;

presenting the plurality of word candidates for selection; and

receiving a user input to select one from the plurality of word candidates.

14. The method of claim 13, further comprising the step of:

predicting one or more word candidates based on the selected one in anticipation of a user input of a next word.

15. The method of claim 13, wherein the plurality of word candidates are presented in an order of likelihood of matching to the user input of the word.

16. The method of claim 1, further comprising the steps of:

automatically selecting a most likely one from the one or more word candidates as a recognized word for the user input of the word;

predicting one or more word candidates based on the most likely one in anticipation of a user input of a next word.

17. The method of claim 1, further comprising any of the steps of:

automatically accenting one or more characters;

automatically capitalizing one or more characters;

automatically adding one or more punctuation symbols; and

automatically adding one or more delimiters.

18. The method of claim 1, wherein each of the plurality of recognition results comprises a plurality of probability indicators associated with a plurality of word component candidates, respectively, to indicate relative likelihood of matching a portion of the user input.

19. A machine readable medium containing instruction data which when executed on a data processing system causes the system to perform a method for recognizing language input, the method comprising the steps of:

processing a user input of a word of a language by performing pattern recognition to generate a plurality of recognition results for a plurality of word components, respectively, at least one of the plurality of recognition results comprising a plurality of word component candidates and a plurality of probability indicators, the plurality of probability indicators indicating degrees of probability of matching of the plurality of word components to a portion of the user input relative to each other; and

determining one or more word candidates for the user input of the word from the plurality of recognition results and from data indicating probability of usage of a list of words.

20. The medium of claim 19, wherein the one or more word candidates comprise a plurality of word candidates;

and the method further comprises the steps of;

presenting the plurality of word candidates for selection;

receiving a user input to select one from the plurality of word candidates; and

predicting one or more word candidates based on the selected one in anticipation of a user input of a next word.

21. The medium of claim 19, the method further comprising the steps of:

automatically selecting a most likely one from the one or more word candidates as a recognized word for the user input of the word; and

predicting one or more word candidates based on the most likely one in anticipation of a user input of a next word.

22. A data processing system for recognizing language input, comprising:

means for processing a user input of a word of a language through pattern recognition to generate a plurality of recognition results for a plurality of word components respectively, at least one of the plurality of recognition results comprising a plurality of word component candidates and a plurality of probability indicators, the plurality of probability indicators indicating degrees of probability of matching of the plurality of word components to a portion of the user input relative to each other; and

means for determining one or more word candidates for the user input of the word from the plurality of recognition results and from data indicating probability of usage of a list of words.

23. The data processing system of claim 22, wherein the one or more word candidates comprise a plurality of word candidates;

and the system further comprises;

means for presenting the plurality of word candidates for selection; and

means for receiving a user input to select one from the plurality of word candidates; and

wherein the plurality of word candidates are presented in an order of likelihood of matching to the user input of the word.

24. The data processing system of claim 22, wherein each of the plurality of recognition results comprises a plurality of probability indicators associated with a plurality of word component candidates respectively to indicate relative likelihood of matching a portion of the user input.

25. The data processing system of claim 22, further comprising means for any of:

automatically accenting one or more characters;

automatically capitalizing one or more characters;

automatically adding one or more punctuation symbols; and

automatically adding one or more delimiters.

26. The data processing system of claim 22, wherein selection of the plurality of word candidates causes the pattern recognition to adjust subsequent probability indicators for one or more word components of the selected plurality of word candidates.