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Auto-Correction for Freeform Text Input Containing Special Characters that Follow a Common Pattern

IP.com Disclosure Number: IPCOM000248756D
Publication Date: 2017-Jan-06
Document File: 2 page(s) / 62K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed is a system to provide auto-correction for freeform text input containing special characters that follow a common pattern.

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Auto-Correction for Freeform Text Input Containing Special Characters that Follow a Common Pattern

Auto-correction technologies today exist for a number of languages. No prior art exists that addresses providing auto-correction for special characters such as symbols and signs.

For example, current auto-correction technologies do not provide any suggestions for the following types of entries: • Monetary value: $10/94 to $10.94 • Phone number: 905-413=5027 to 905-413-5027 • Email address: me#iamuser.com to me@iamuser.com • URL: http:/www.ibm.com to http://www.ibm.com

The novel contribution is a system to provide auto-correction for freeform text input containing special characters that follow a common pattern (e.g., @,-,/,.etc.).

Patterns that follow standard conventions that contain special characters include, but are not limited to: • Phone Numbers: XXX-XXX-XXXX | (XXX)-XXX-XXXX • Email addresses: username@domain.com • Monetary values: $XX.XX • Websites/Uniform Resource Locators (URLs): http://www.ibm.com/us-en/ • Hashtags: #description

The novel system considers the globalization/location aspect of the input strings. For example, when examining the dollar sign that is entered in the Canadian locale, the dollar sign should be entered after the currency amount (e.g., 20$).

The novel system also utilizes the speech-to-text conversion technique when examining the voice-based speech. For example, the user says an email address is: first name dot last name AT us dot company name dot com. The system can intelligently convert the speech to text to use the @ symbol rather than the string AT by evaluating the context.

In an example embodiment, User A texts User B from China and asks how much tip to give in the restaurant or to the taxi driver. User B has no idea, so calls User C. While getting answers on the phone from User C, User B types the message t...