Library of existing spoken dialog data for use in generating new natural language spoken dialog systems

• US 10,199,039 B2
• Filed: 12/09/2015
• Issued: 02/05/2019
• Est. Priority Date: 01/05/2005
• Status: Expired due to Fees

• Current Assignee: Nuance Communications, Inc. (Microsoft Corporation)
• Original Assignee: Nuance Communications, Inc. (Microsoft Corporation)
• Inventors: Begeja, Lee, Di Fabbrizio, Giuseppe, Gibbon, David Crawford, Hakkani-Tur, Dilek Z., Liu, Zhu, Renger, Bernard S., Shahraray, Behzad, Tur, Gokhan
• Primary Examiner(s): Ortiz-Sanchez, Michael
• Application Number:
  US14/963,408
• Publication Number:
  US 20160093300A1
• Time in Patent Office: 1,154 Days
• CPC Class Codes: G10L 15/063 Training
• CPC Class Codes: G10L 15/1815 Semantic context, e.g. disambiguation of the recognition hypotheses based on word meaning
• CPC Class Codes: G10L 15/22 Procedures used during a speech recognition process, e.g. man-machine dialogue
• CPC Class Codes: G10L 15/28 Constructional details of speech recognition systems
• CPC Class Codes: G10L 25/48 specially adapted for particular use

Abstract

A machine-readable medium may include a group of reusable components for building a spoken dialog system. The reusable components may include a group of previously collected audible utterances. A machine-implemented method to build a library of reusable components for use in building a natural language spoken dialog system may include storing a dataset in a database. The dataset may include a group of reusable components for building a spoken dialog system. The reusable components may further include a group of previously collected audible utterances. A second method may include storing at least one set of data. Each one of the at least one set of data may include ones of the reusable components associated with audible data collected during a different collection phase.

Claims

1. A method comprising:

collecting, via a plurality of industry specific spoken dialog systems and during a plurality of collection phases comprising respective defined periods of time and in which respective conversations between a user and a respective industry specific spoken dialog system of the plurality of industry specific spoken dialog systems occurs, a plurality of audible utterances for each respective conversation;

organizing, via a processor, the plurality of audible utterances into a plurality of datasets having call-type labels, wherein each dataset in the plurality of datasets pertains to a unique industrial sector in a plurality of industrial sectors;

identifying a positive example utterance for each of the call-type labels;

generating a natural language spoken dialog system using the plurality of datasets and the positive example utterance for each of the call-type labels;

receiving audible speech at the natural language spoken dialog system; and

converting the audible speech into text via the natural language spoken dialog system.

2. The method of claim 1, further comprising, prior to the generating of the natural language spoken dialog system, comparing, for each of the call-type labels, each utterance in the plurality of audible utterances to a negative example utterance for an associated call-type.

3. The method of claim 1, wherein organizing of the plurality of audible utterances further comprises using a corresponding industry specific spoken dialog system of the plurality of industry specific spoken dialog systems.

4. The method of claim 3, wherein the corresponding industry specific spoken dialog system and the unique industrial sector share a common task domain.

5. The method of claim 1, wherein the plurality of datasets are stored in an extensible markup language database.

6. The method of claim 1, wherein the plurality of datasets are stored in a relational database.

7. The method of claim 1, wherein utterances in the plurality of audible utterances are each associated with a respective utterance-type category.

8. A system comprising:

a processor; and

a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising;

collecting, via a plurality of industry specific spoken dialog systems and during a plurality of collection phases comprising respective defined periods of time and in which respective conversations between a user and a respective industry specific spoken dialog system of the plurality of industry specific spoken dialog systems occurs, a plurality of audible utterances for each respective conversation;

organizing the plurality of audible utterances into a plurality of datasets having call-type labels, wherein each dataset in the plurality of datasets pertains to a unique industrial sector in a plurality of industrial sectors;

identifying a positive example utterance for each of the call-type labels;

generating a natural language spoken dialog system using the plurality of datasets and the positive example utterance for each of the call-type labels;

receiving audible speech at the natural language spoken dialog system; and

converting the audible speech into text via the natural language spoken dialog system.

9. The system of claim 8, the computer-readable storage medium having additional instructions stored which, when executed by the processor, cause the processor to perform operations comprising:

prior to the generating of the natural language spoken dialog system, comparing, for each of the call-type labels, each utterance in the plurality of audible utterances to a negative example utterance for an associated call-type.

10. The system of claim 8, wherein organizing of the plurality of audible utterances further comprises using a corresponding industry specific spoken dialog system of the plurality of industry specific spoken dialog systems.

11. The system of claim 10, wherein the corresponding industry specific spoken dialog system and the unique industrial sector share a common task domain.

12. The system of claim 8, wherein the plurality of datasets are stored in an extensible markup language database.

13. The system of claim 8, wherein the plurality of datasets are stored in a relational database.

14. The system of claim 8, wherein utterances the plurality of audible utterances are each associated with a respective utterance-type category.

15. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising:

collecting, via a plurality of industry specific spoken dialog systems and during a plurality of collection phases comprising respective defined periods of time and in which respective conversations between a user and a respective industry specific spoken dialog system of the plurality of industry specific spoken dialog systems occurs, a plurality of audible utterances for each respective conversation;

organizing the plurality of audible utterances into a plurality of datasets having call-type labels, wherein each dataset in the plurality of datasets pertains to a unique industrial sector in a plurality of industrial sectors;

identifying a positive example utterance for each of the call-type labels;

generating a natural language spoken dialog system using the plurality of datasets and the positive example utterance for each of the call-type labels;

receiving audible speech at the natural language spoken dialog system; and

converting the audible speech into text via the natural language spoken dialog system.

16. The computer-readable storage device of claim 15, having additional instructions stored which, when executed by the computing device, cause the computing device to perform operations comprising:

prior to the generating of the natural language spoken dialog system, comparing, for each of the call-type labels, each utterance in the plurality of audible utterances to a negative example utterance for an associated call-type.

17. The computer-readable storage device of claim 15, wherein organizing of the plurality of audible utterances further comprises using a corresponding industry specific spoken dialog system of the plurality of industry specific spoken dialog systems.

18. The computer-readable storage device of claim 17, wherein the corresponding industry specific spoken dialog system and the unique industrial sector share a common task domain.

19. The computer-readable storage device of claim 15, wherein the plurality of datasets are stored in an extensible markup language database.

20. The computer-readable storage device of claim 15, wherein the plurality of datasets are stored in a relational database.