The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Apr. 26, 2011
Filed:
Mar. 18, 2004
Lee Begeja, Gillette, NJ (US);
Mazin G. Rahim, Warren, NJ (US);
Allen Louis Gorin, Berkeley Heights, NJ (US);
Behzad Shahraray, Freehold, NJ (US);
David Crawford Gibbon, Lincroft, NJ (US);
Zhu Liu, Marlboro, NJ (US);
Bernard S. Renger, New Providence, NJ (US);
Patrick Guy Haffner, Atlantic Highlands, NJ (US);
Harris Drucker, Long Branch, NJ (US);
Steven Hart Lewis, Middletown, NJ (US);
Lee Begeja, Gillette, NJ (US);
Mazin G. Rahim, Warren, NJ (US);
Allen Louis Gorin, Berkeley Heights, NJ (US);
Behzad Shahraray, Freehold, NJ (US);
David Crawford Gibbon, Lincroft, NJ (US);
Zhu Liu, Marlboro, NJ (US);
Bernard S. Renger, New Providence, NJ (US);
Patrick Guy Haffner, Atlantic Highlands, NJ (US);
Harris Drucker, Long Branch, NJ (US);
Steven Hart Lewis, Middletown, NJ (US);
AT&T Intellectual Property II, L.P., Atlanta, GA (US);
Abstract
A system and method is provided for rapidly generating a new spoken dialog application. In one embodiment, a user experience person labels the transcribed data (e.g., 3000 utterances) using a set of interactive tools. The labeled data is then stored in a processed data database. During the labeling process, the user experience person not only groups utterances in various call type categories, but also flags (e.g., 100-200) specific utterances as positive and negative examples for use in an annotation guide. The labeled data in the processed data database can also be used to generate an initial natural language understanding (NLU) model.