LANGUAGE INPUT CORRECTION

• US 20160357304A1
• Filed: 09/03/2015
• Published: 12/08/2016
• Est. Priority Date: 06/05/2015
• Status: Active Grant

• Current Assignee: Apple Inc.
• Original Assignee: Apple Inc.
• Inventors: HATORI, Jun, YU, Dominic
• Granted Patent: US 10,101,822 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 3/0237 using prediction or retrieval techniques
• 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

Abstract

The present disclosure generally relates to language input correction. In one example process, a sequence of contact inputs can be detected via a keyboard interface on a touch-sensitive display. A contact input of the sequence of contact inputs can include a contact motion from a first position to a second position of the keyboard interface. A plurality of candidate words corresponding to the sequence of contact inputs can be determined. The plurality of candidate words can be ranked based on a probability that the contact input is an intended input to select a first key of the keyboard interface, and a probability that the contact input is an intended input to select a second key of the keyboard interface. A portion of the plurality of candidate words can be displayed for user selection.

Claims

1. A method for inputting language, the method comprising:

at a device having one or more processors, memory, and a touch-sensitive display;

detecting a sequence of contact inputs via a keyboard interface on the touch-sensitive display, wherein a contact input of the sequence of contact inputs comprises a contact motion from a first position to a second position of the keyboard interface;

determining a plurality of candidate words corresponding to the sequence of contact inputs;

ranking the plurality of candidate words based on a probability that the contact input is an intended input to select a first key of the keyboard interface, and a probability that the contact input is an intended input to select a second key of the keyboard interface; and

displaying a portion of the plurality of candidate words for user selection.

2. The method of claim 1, wherein the first key corresponds to a first writing symbol of a language and the second key corresponds to a second writing symbol of the language.

3. The method of claim 1, wherein the plurality of candidate words includes words of a first writing system and words of a second writing system.

4. The method of claim 1, further comprising:

determining a plurality of character strings that potentially correspond to the sequence of contact inputs; and

determining, using a geometry model, a probability of each character string of the plurality of character strings given the sequence of contact inputs, wherein the plurality of candidate words is determined from the plurality of character strings based on the probability of each character string of the plurality of character strings given the sequence of contact inputs.

5. The method of claim 1, wherein the plurality of candidate words are determined based on a lexicon of a language model.

6. The method of claim 1, wherein:

the probability that the contact input is an intended input to select the first key of the keyboard interface is determined based on a distance between the first position and a center position of the first key; and

the probability that the contact input is an intended input to select the second key of the keyboard interface is determined based on a distance between the first position and a center position of the second key.

7. The method of claim 1, wherein the probability that the contact input is an intended input to select the first key of the keyboard interface and the probability that the contact input is an intended input to select the second key of the keyboard interface are each determined based on a distance between the first position and the second position of the contact motion.

8. The method of claim 1, further comprising:

determining a probability of each candidate word given the sequence of contact inputs, wherein ranking the plurality of candidate words is based on the probability of each candidate word given the sequence of contact inputs.

9. The method of claim 8, wherein the probability of each candidate word of the plurality of candidate words given the sequence of contact inputs is determined based on a probability of a respective character string of the plurality of character strings given the sequence of contact inputs.

10. The method of claim 8, further comprising:

determining a probability of each candidate word of the plurality of candidate words given a respective character string of the plurality of character strings, wherein the probability of each candidate word of the plurality of candidate words given the sequence of contact inputs is determined based on the probability of each candidate word of the plurality of candidate words given a respective character string of the plurality of character strings.

11. The method of claim 10, wherein the probability of each candidate word of the plurality of candidate words given a respective character string of the plurality of character strings is determined using one or more language models.

12. The method of claim 1, wherein the plurality of candidate words is determined using a lexicon with a trie data structure.

13. The method of claim 1, wherein the plurality of candidate words is ranked based on a distance between the first position and a center position of each key on the keyboard interface.

14. The method of claim 1, wherein the plurality of candidate words is ranked based on a distance between the first position and the second position of the contact motion.

15. The method of claim 1, wherein the plurality of candidate words is ranked based on a speed of the contact motion from the first position and the second position.

16. The method of claim 1, wherein the plurality of candidate words is ranked based on an angle of the contact motion with respect to a reference axis of the keyboard interface.

17. The method of claim 1, wherein the keyboard interface is a 10-key kana keyboard interface.

18. A non-transitory computer-readable storage medium comprising computer-executable instructions, which when executed by one or more processors, cause the one or more processors to:

detect a sequence of contact inputs via a keyboard interface on the touch-sensitive display, wherein a contact input of the sequence of contact inputs comprises a contact motion from a first position to a second position of the keyboard interface;

determine a plurality of candidate words corresponding to the sequence of contact inputs;

rank the plurality of candidate words based on a probability that the contact input is an intended input to select a first key of the keyboard interface, and a probability that the contact input is an intended input to select a second key of the keyboard interface; and

display a portion of the plurality of candidate words for user selection.

19. A system comprising:

one or more processors;

memory storing computer-readable instructions, which when executed by the one or more processors, cause the one or more processors to;

detect a sequence of contact inputs via a keyboard interface on the touch-sensitive display, wherein a contact input of the sequence of contact inputs comprises a contact motion from a first position to a second position of the keyboard interface;

determine a plurality of candidate words corresponding to the sequence of contact inputs;

rank the plurality of candidate words based on a probability that the contact input is an intended input to select a first key of the keyboard interface, and a probability that the contact input is an intended input to select a second key of the keyboard interface; and

display a portion of the plurality of candidate words for user selection.

20. The system of claim 19, wherein the computer-readable instructions further cause the one or more processors to:

determine a plurality of character strings that potentially correspond to the sequence of contact inputs; and

determine, using a geometry model, a probability of each character string of the plurality of character strings given the sequence of contact inputs, wherein the plurality of candidate words is determined from the plurality of character strings based on the probability of each character string of the plurality of character strings given the sequence of contact inputs.

21. The system of claim 19, wherein:

the probability that the contact input is an intended input to select the first key of the keyboard interface is determined based on a distance between the first position and a center position of the first key; and

the probability that the contact input is an intended input to select the second key of the keyboard interface is determined based on a distance between the first position and a center position of the second key.

22. The system of claim 19, wherein the probability that the contact input is an intended input to select the first key of the keyboard interface and the probability that the contact input is an intended input to select the second key of the keyboard interface are each determined based on a distance between the first position and the second position of the contact motion.

23. The system of claim 19, wherein the computer-readable instructions further cause the one or more processors to:

determine a probability of each candidate word given the sequence of contact inputs, wherein ranking the plurality of candidate words is based on the probability of each candidate word given the sequence of contact inputs.

24. The system of claim 23, wherein the probability of each candidate word of the plurality of candidate words given the sequence of contact inputs is determined based on a probability of a respective character string of the plurality of character strings given the sequence of contact inputs.

25. The system of claim 23, wherein the computer-readable instructions further cause the one or more processors to:

determine a probability of each candidate word of the plurality of candidate words given a respective character string of the plurality of character strings, wherein the probability of each candidate word of the plurality of candidate words given the sequence of contact inputs is determined based on the probability of each candidate word of the plurality of candidate words given a respective character string of the plurality of character strings.