User-centric soft keyboard predictive technologies

• US 8,782,556 B2
• Filed: 03/22/2010
• Issued: 07/15/2014
• Est. Priority Date: 02/12/2010
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Corporation
• Inventors: Badger, Eric Norman, Linerud, Drew Elliot, Almog, Itai, Paek, Timothy S., Sundararajan, Parthasarathy, Rudchenko, Dmytro, Gunawardana, Asela J.
• Primary Examiner(s): ITURRALDE, ENRIQUE W
• Application Number:
  US12/729,130
• Publication Number:
  US 20110202876A1
• Time in Patent Office: 1,576 Days
• Field of Search: 715/256, 715/257, 715259-263, 715/271, 715/705, 715/707, 715/708, 715/710, 715/711, 715/713, 715/714, 715/715, 715/764, 715/780, 715/808, 715/809, 715/810, 715/811, 715/812, 715/816, 715/825, 715/863, 715/864, 715/866, 704/10, 382224-231
• US Class Current: 715/816
• CPC Class Codes: G06F 16/35 Clustering; Classification
• CPC Class Codes: G06F 3/0237 using prediction or retrieval techniques
• CPC Class Codes: G06F 3/048 Interaction techniques based on graphical user interfaces [GUI]
• CPC Class Codes: G06F 3/04883 for inputting data by handwriting, e.g. gesture or text
• CPC Class Codes: G06F 3/04886 by partitioning the display area of the touch-screen or the surface of the digitising tablet into independently controllable areas, e.g. virtual keyboards or menus
• CPC Class Codes: G06F 40/166 Editing, e.g. inserting or deleting
• CPC Class Codes: G06F 40/247 Thesauruses; Synonyms
• CPC Class Codes: G06F 40/274 Converting codes to words; Guess-ahead of partial word inputs
• CPC Class Codes: G06N 20/00 Machine learning

Abstract

An apparatus and method are disclosed for providing feedback and guidance to touch screen device users to improve text entry user experience and performance by generating input history data including character probabilities, word probabilities, and touch models. According to one embodiment, a method comprises receiving first input data, automatically learning user tendencies based on the first input data to generate input history data, receiving second input data, and generating auto-corrections or suggestion candidates for one or more words of the second input data based on the input history data. The user can then select one of the suggestion candidates to replace a selected word with the selected suggestion candidate.

Claims

1. A method, comprising:

receiving first input data;

automatically learning user tendencies based on the first input data to generate input history data;

receiving second input data with a touch screen keyboard and displaying one or more words of the second input data on a touch screen display associated with the touch screen keyboard, wherein the receiving second input data further comprises non-uniformly resizing a first and a second target area of the touch screen keyboard based on a probability that a key associated with the first target area has a different probability than a key associated with the second target area; and

one or more characters of the second input data are determined at least in part using the first resized target area, the second resized target area, or the first and the second resized target areas.

2. The method of claim 1, wherein the receiving first input data comprises receiving a completion event indicating that the first input data is complete, wherein the completion event is associated with the sending of a text message, instant message, or email.

3. The method of claim 1, wherein the automatically learning user tendencies comprises analyzing user-specific web content associated with a user.

4. The method of claim 1, wherein the input history data includes touch position data for one or more key presses received using a touch screen keyboard.

5. The method of claim 1, wherein:

the first input data comprises a word; and

the input history data comprises data representing the last time a word was used.

6. The method of claim 1, wherein the input history data comprises typing speed data for one or more keystrokes received using a hardware or touch screen keyboard.

7. The method of claim 1, wherein the input history data comprises orientation data representing the orientation of a touch screen as being in a landscape orientation or in a portrait orientation while receiving the first input data.

8. The method of claim 1, wherein:

the first input data and the second input data are received at a computing cloud from a text entry device;

the text entry device is at a location remote from the cloud;

the automatically learning user tendencies occurs in the cloud; and

the generated auto-corrections or suggestion candidates are provided from the cloud to the text entry device.

9. The method of claim 1, wherein the resizing the one or more target areas includes using a generic touch model based on previously-collected touch screen keyboard typing data for plural users, the generic touch model including one or more child probability scores for one or more input data sequences for the typing data.

10. One or more non-transitory computer-readable storage media or memory storing computer-readable instructions that when executed cause a computer to perform a method, the method comprising:

receiving first input data;

automatically learning user tendencies based on the first input data to generate input history data;

receiving second input data with a touch screen keyboard and displaying one or more words of the second input data on a touch screen display associated with the touch screen keyboard, wherein the receiving second input data further comprises non-uniformly resizing a first and a second target area of the touch screen keyboard based on a probability that a key associated with the first target area has a different probability than a key associated with the second target area;

with the touch screen display, receiving touch input over a selected one of the displayed words; and

responsive to the receiving touch input, generating suggestion candidates for the selected word based on the input history data and the second input data.

11. The computer-readable storage media or memory of claim 10, wherein the automatically learning user tendencies comprises analyzing user-specific web content associated with a user.

12. The computer-readable storage media or memory of claim 10, wherein the input history data includes touch position data for one or more key presses received using a touch screen keyboard.

13. The computer-readable storage media or memory of claim 10, wherein the input history data comprises orientation data representing the orientation of a touch screen as being in a landscape orientation or in a portrait orientation while receiving the first input data.

14. The computer-readable storage media or memory of claim 10, wherein:

the receiving second input data further comprises resizing one or more target areas associated with one or more associated keys on a touch screen keyboard based on one or more characters previously received in the second input data; and

one or more characters of the second input data are determined at least in part using the resized target areas.

15. The computer-readable storage media or memory of claim 14, wherein the resizing the one or more target areas includes using a generic touch model based on previously-collected touch screen keyboard typing data for plural users, the generic touch model including one or more child probability scores for one or more input data sequences for the typing data.

16. One or more non-transitory computer-readable storage media or memory storing computer-readable instructions that when executed cause a computer to perform a method, the method comprising:

receiving first input data using a touch screen keyboard;

a step for automatically learning user tendencies based on the first input data to generate input history data, the input history data comprising typing speed data for the received first input data;

a step for receiving second input data with a touch screen keyboard and displaying one or more words of the second input data on a touch screen display associated with the touch screen keyboard, wherein;

the receiving second input data further comprises non-uniformly resizing a first and a second target area of the touch screen keyboard based on a probability that a key associated with the first target area has a different probability than a key associated with the second target area;

with the touch screen display, receiving touch input over a selected one of the displayed words; and

responsive to the receiving touch input, generating suggestion candidates for the selected word based on the input history data and the second input data, the second input data comprising typing speed data for the received second input data.

17. One or more non-transitory computer-readable storage media or memory storing computer-readable instructions that when executed cause a computer to perform a method, the method comprising:

receiving first input data;

automatically learning user tendencies based on the first input data to generate input history data;

receiving second input data with a touch screen keyboard by non-uniformly resizing a first and a second target area of the touch screen keyboard, wherein the non-uniform resizing is based on a probability that a key associated with the first target area has a different probability than a key associated with the second target area;

displaying one or more words of the second input data on a touch screen display;

with the touch screen display, receiving touch input over a selected one of the displayed words; and

responsive to the receiving touch input, generating auto-corrections or suggestion candidates for the selected word based on the input history data and the second input data.

18. The non-transitory computer-readable storage media or memory of claim 17, wherein the resized target areas include two or more zones, each of the zones for a respective target area being associated with a different language model probability of a respective associated key being correct.

19. The non-transitory computer-readable storage media or memory of claim 17, wherein:

the input history data comprises orientation data representing the orientation of a touch screen display as being in a landscape orientation or in a portrait orientation while receiving the first input data; and

at least one of the different language model probabilities is different when the touch screen is detected as being in a landscape orientation than when the touch screen display is detected as being in a portrait orientation.

20. The non-transitory computer-readable storage media or memory of claim 17, wherein the input history data includes touch position data for one or more key presses received using a touch screen keyboard.

21. A method, comprising:

receiving first input data;

automatically learning user tendencies based on the first input data to generate input history data;

receiving second input data with a touch screen keyboard by non-uniformly resizing a first and a second target area of the touch screen keyboard with the touch screen display, the resizing including using a generic touch model based on previously-collected touch screen keyboard typing data for plural users, the generic touch model including one or more child probability scores for one or more input data sequences for the typing data;

receiving touch input over a selected one of the displayed words; and

responsive to the receiving touch input, generating auto-corrections or suggestion candidates for the selected word based on the input history data and the second input data.

22. The method of claim 21, wherein the resized target areas include two or more zones, each of the zones for a respective target area being associated with a different language model probability of a respective associated key being correct.

23. The method of claim 21, wherein the generic touch model is based at least in part on simulation run using varying touch model parameters and replayed logged touch data.

24. The method of claim 21, wherein the input history data includes touch position data for one or more key presses received using a touch screen keyboard.

25. The method of claim 21, wherein the touch screen display provides no visual indication of the dimensions of the first and second target areas.