IP Library Granted Patent US 7,319,957
Granted Patent B2
US 7,319,957 · App. 11/043,506 · Granted Jan 15, 2008

Handwriting and voice input with automatic correction

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Quick Facts
Patent No.
US 7,319,957
App. No.
11/043,506
Granted
Jan 15, 2008
Kind
B2
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 (69)

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

receiving a plurality of recognition results for a plurality of word components, respectively, for processing a user input of a partial word of a language, 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

predicting one or more word candidates that complete the partial 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 said word component candidates comprise any of:

a stroke from handwriting recognition, speech recognition or keypad entry;

a character from handwriting recognition, speech recognition or keypad entry;

a phoneme from handwriting recognition, speech recognition or keypad entry; and

a syllable or other phonetic representation from handwriting recognition, speech recognition or from keypad entry.

3. The method of claim 1 , wherein said language is any of:

alphabetical; and

ideographic.

4. The method of claim 1 , wherein the step of determining one or more word candidates further comprises the step of:

eliminating a plurality of combinations of word component candidates of the plurality of recognition results.

5. The method of claim 4 , wherein the step of determining one or more word candidates further comprises the step of:

selecting a plurality of word candidates from a list of words of the language, the plurality of word candidates containing combinations of word component candidates of the plurality of recognition results.

6. The method of claim 5 , further comprising the step of:

determining one or more likelihood indicators for the one or more word candidates to indicate relative possibilities of matching to the user input of the word from the plurality of recognition results and from data indicating probability of usage of a list of words.

7. The method of claim 6 , further comprising the step of:

sorting the one or more word candidates according to the one or more likelihood indicators.

8. The method of claim 7 , further comprising the step of:

automatically selecting one word from the one or more word candidates.

9. The method of claim 8 , wherein the step of

automatically selecting is performed on any of:

phrases in the language;

word pairs in the language; and

word trigrams in the language.

10. The method of claim 8 , wherein the step of automatically selecting is performed based on any of:

morphology of the language; and

grammatical rules of the language.

11. The method of claim 8 , wherein the step of automatically selecting is performed according to a context in which the user input of the word is received.

12. The method of claim 8 , further comprising the step of:

predicting a plurality of word candidates based on a word that is automatically selected in anticipation of a user input of a next word.

13. The method of claim 7 , further comprising the steps of:

presenting the one or more word candidates for user selection; and

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

14. The method of claim 13 , wherein the plurality of word candidates are presented in an order according to the one or more likelihood indicators.

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

predicting a plurality of word candidates based on the word selected in anticipation of a user input of a next word.

16. 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.

17. 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.

18. 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.

19. A machine readable medium containing instruction data which when executed on a data processing system causes the system to perform a method for processing language input, the method comprising the steps of: receiving a plurality of recognition results for a plurality of word components, respectively, for processing a user input of a partial word of a language, 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

predicting one or more word candidates that complete the partial 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 step of determining one or more word candidates comprises the steps of:

eliminating a plurality of combinations of word component candidates of the plurality of recognition results; and

selecting a plurality of word candidates from a list of words of the language, the plurality of word candidates containing combinations of word component candidates of the plurality of recognition results.

21. The medium of claim 20 , the method further comprising the steps of:

determining one or more likelihood indicators for the one or more word candidates to indicate relative possibilities of matching to the user input of the word from the plurality of recognition results and from data indicating probability of usage of a list of words;

sorting the one or more word candidates according to the one or more likelihood indicators; automatically selecting one from the one or more word candidates; and

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

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

means for receiving a plurality of recognition results for a plurality of word components respectively for processing a user input of a partial word of a language, 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 that complete the partial 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 means for determining one or more word candidates comprises:

means for eliminating a plurality of combinations of word component candidates of the plurality of recognition results; and

means for selecting a plurality of word candidates from a list of words of the language, the plurality of word candidates containing combinations of word component candidates of the plurality of recognition results.

24. The data processing system of claim 23 , further comprising:

means for determining one or more likelihood indicators for the one or more word candidates to indicate relative possibilities of matching to the user input of the word from the plurality of recognition results and from data indicating probability of usage of a list of words;

means for sorting the one or more word candidates according to the one or more likelihood indicators; means for presenting the one or more word candidates for user selection; and

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

means for predicting a plurality of word candidates based on the selected one in anticipation of a user input of a next word;

wherein the plurality of word candidates are presented in an order according to the one or more likelihood indicators.

25. The data processing system of claim 22 , further comprising means for: predicting a plurality of word candidates based on the word selected in anticipation of a user input of a next word.

Assignments (12)
RELEASE (REEL 052935 / FRAME 0584) Recorded Jan 2, 2025
From: WELLS FARGO BANK, NATIONAL ASSOCIATION
To: CERENCE OPERATING COMPANY
Reel/Frame 069797/0818 →
CORRECTIVE ASSIGNMENT TO CORRECT THE REPLACE THE CONVEYANCE DOCUMENT WITH THE NEW ASSIGNMENT PREVIOUSLY RECORDED AT REEL: 050836 FRAME: 0191. ASSIGNOR(S) HEREBY CONFIRMS THE ASSIGNMENT. Recorded Apr 19, 2022
From: NUANCE COMMUNICATIONS, INC.
To: CERENCE OPERATING COMPANY
Reel/Frame 059804/0186 →
SECURITY AGREEMENT Recorded Jun 15, 2020
From: CERENCE OPERATING COMPANY
To: WELLS FARGO BANK, N.A.
Reel/Frame 052935/0584 →
RELEASE OF SECURITY INTEREST Recorded Jun 12, 2020
From: BARCLAYS BANK PLC
To: CERENCE OPERATING COMPANY
Reel/Frame 052927/0335 →
SECURITY AGREEMENT Recorded Nov 7, 2019
From: CERENCE OPERATING COMPANY
To: BARCLAYS BANK PLC
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CORRECTIVE ASSIGNMENT TO CORRECT THE ASSIGNEE NAME PREVIOUSLY RECORDED AT REEL: 050836 FRAME: 0191. ASSIGNOR(S) HEREBY CONFIRMS THE INTELLECTUAL PROPERTY AGREEMENT. Recorded Oct 29, 2019
From: NUANCE COMMUNICATIONS, INC.
To: CERENCE OPERATING COMPANY
Reel/Frame 050871/0001 →
INTELLECTUAL PROPERTY AGREEMENT Recorded Oct 23, 2019
From: NUANCE COMMUNICATIONS, INC.
To: CERENCE INC.
Reel/Frame 050836/0191 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jan 23, 2014
From: TEGIC INC.
To: NUANCE COMMUNICATIONS, INC.
Reel/Frame 032122/0269 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jun 13, 2007
From: AOL LLC, A DELAWARE LIMITED LIABILITY COMPANY (FORMERLY KNOWN AS AMERICA ONLINE, INC.)
To: TEGIC COMMUNICATIONS, INC.
Reel/Frame 019425/0489 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 23, 2007
From: AMERICA ONLINE, INC.
To: AOL LLC, A DELAWARE LIMITED LIABILITY COMPANY (FORMERLY KNOWN AS AMERICA ONLINE, INC.)
Reel/Frame 018923/0517 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Feb 1, 2007
From: AMERICA ONLINE, INC.
To: AOL LLC
Reel/Frame 018837/0141 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 10, 2005
From: ROBINSON, ALEX; BRADFORD, ETHAN; KAY, DAVID; VAN MEURS, PIM; STEPHANICK, JAMES
To: AMERICA ONLINE, INCORPORATED
Reel/Frame 015989/0542 →