Context based customization of word assistance functions

Patent metadata

Field	Value
Publication number	US-9613022-B2
Application number	US-201514614084-A
Country	US
Kind code	B2
Filing date	Feb 4, 2015
Priority date	Feb 4, 2015
Publication date	Apr 4, 2017
Grant date	Apr 4, 2017

Abstract

For generating customized word assistance functions based on user information and context, a system, apparatus, method, and computer program product are disclosed. The apparatus includes a processor and a memory that stores code executable by the processor, including code that accesses personal information of a user, identifies a dialectal nuance of the user based on the personal information, and selects a word recognition dictionary based on the dialectal nuance. The dialectal nuance may be based on a location of the user, a nationality of the user, an age of the user, an education level of the user, and/or a profession of the user. The apparatus may also suggest one or more text entries from the selected word recognition dictionary based on the user input.

First claim

What is claimed is:

1. An apparatus comprising:
an input device that receives user input;
a processor;
a memory that stores code executable by the processor to:
accesses personal information of a user of the apparatus, the personal information including an education level and profession of the user;
identify a dialectal nuance of the user based on the personal information, the dialectal nuance indicating a propensity to use abbreviations, slang, and technical jargon;
select a word recognition dictionary from a plurality of word recognition dictionaries based on the dialectal nuance, the selected word recognition dictionary including abbreviations, slang, and technical jargon as indicated by the dialectal nuance;
suggest one or more text entries from the selected word recognition dictionary based on user input of a partial word;
receives user input of a complete word;
determines whether the complete word matches the dialectal nuance; and
suggests at least one alternative term from the selected word recognition dictionary in response to the complete word not matching the dialectal nuance.

2. The apparatus of claim 1 , wherein the processor further retrieves the personal information from a networked data storage device.

3. The apparatus of claim 1 , wherein the processor further:
determines whether a message recipient is a contact of the user based on the personal information; and
retrieves the user's contact information for the message recipient, wherein selecting the word recognition dictionary comprises selecting the word recognition dictionary based on the contact information.

4. The apparatus of claim 1 , wherein the processor further:
identifies a message recipient; and
determines a geographic location of the message recipient, wherein the word recognition dictionary is updated to include dialect used in the geographic location of the recipient.

5. The apparatus of claim 1 , wherein the processor further:
identifies a message recipient; and
determines a relationship type between the user and the message recipient based on the personal information, wherein selecting the word recognition dictionary comprises selecting the word recognition dictionary based on the determined relationship type.

6. The apparatus of claim 1 , wherein the dialectal nuance is further based on one or more of a location of the user, a nationality of the user, and an age of the user.

7. A method comprising:
receiving text input from a device user;
accessing, by use of a processor, personal information for the user inputting text, the personal information indicating an education level and a profession of the user;
identifying a dialect trait of the user based on the personal information, the dialect trait indicating an amount of slang, abbreviations, and technical jargon;
selecting a text recognition database from a plurality of text recognition databases based on the dialect trait, the selected text recognition database including abbreviations, slang, and technical jargon as indicated by the dialect trait;
suggesting one or more text entries from the selected text recognition database based on a partial word of the input text; determining whether a complete word of the text input matches the dialect trait; and
suggesting at least one alternative term from the selected text recognition database in response to the complete word not matching the dialect trait.

8. The method of claim 7 , further comprising:
receiving, from the user, a manual correction to a word from the selected text recognition database;
updating the personal information for the user based on the correction; and
reselecting the dialectal trait based on the updated personal information.

9. The method of claim 7 , further comprising identifying a social context for the inputted text, wherein selecting the text recognition database is further based on the social context.

10. The method of claim 7 , further comprising identifying an application receiving the inputted text, wherein identifying a dialect trait comprises determining a dialect trait based on a social setting associated with the identified application.

11. The method of claim 7 , further comprising identifying a message recipient associated with the inputted text, wherein identifying a dialect trait comprises determining a dialect trait based on the message recipient.

12. The method of claim 7 , wherein the text recognition database comprises a subset of a dictionary customized by the user, the subset including words and phrases matching the dialect trait.

13. The method of claim 7 , wherein the personal information includes information selected from the group consisting of a location of the user, a nationality of the user, a native language of the user, a native dialect of the user, and an age of the user.

14. A program product comprising a non-transitory computer readable storage medium that stores code executable by a processor, the executable code comprising code to perform:
receiving input text from a user of a device;
accessing a personal information associated with the user, the personal information including an education level and profession of the user;
determining a lexical context based on the personal information, the lexical context indicating a propensity to use abbreviations, slang, and technical jargon;
selecting a word assistance library from a plurality of word assistance libraries based on the lexical context, the selected word recognition dictionary including abbreviations, slang, and technical jargon as indicated by the dialectal nuance;
determining whether a complete word of the input text matches the lexical context; and
suggesting at least one alternative term from the word assistance library in response to the a complete word not matching the lexical context.

15. The program product of claim 14 , wherein personal information comprises a current location of the user and selecting a word assistance library comprises selecting a word assistance library including a dialect of a geographical region associated with the current location of the user.

Assignees

• Lenovo Singapore Pte Ltd
• Lenovo Singapore Pte Ltd

Inventors

• Stewart Aaron Michael
• Skinner Jeffrey E
• Yu Jonathan Jen-Wei

Classifications

• G06F40/263 Primary

  Language identification · CPC title

• G06F40/232 Primary

  Orthographic correction, e.g. spell checking or vowelisation · CPC title

• G06F40/274

  Converting codes to words; Guess-ahead of partial word inputs · CPC title

• G06F17/273 Primary

  Physics · mapped topic

• G06F17/276

  Physics · mapped topic