BETTER RESOLUTION WHEN REFERENCING TO CONCEPTS

• US 20150348549A1
• Filed: 09/29/2014
• Published: 12/03/2015
• Est. Priority Date: 05/30/2014
• Status: Active Grant

• Current Assignee: Apple Inc.
• Original Assignee: Apple Inc.
• Inventors: TREADGOLD, Nicholas K., GIULI, Richard D.
• Granted Patent: US 9,633,004 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 16/3329 Natural language query formulation or dialogue systems
• CPC Class Codes: G06F 3/167 Audio in a user interface, e.g. using voice commands for navigating, audio feedback
• CPC Class Codes: G06F 40/30 Semantic analysis
• CPC Class Codes: G10L 15/1815 Semantic context, e.g. disambiguation of the recognition hypotheses based on word meaning
• CPC Class Codes: G10L 15/1822 Parsing for meaning understanding
• CPC Class Codes: G10L 15/22 Procedures used during a speech recognition process, e.g. man-machine dialogue
• CPC Class Codes: G10L 2015/223 Execution procedure of a spoken command

Abstract

Systems and processes for operating a virtual assistant programmed to refer to shared domain concepts using concept nodes are provided. In some examples, to process a textual representation of user speech using an active ontology having these concept nodes, a primary user intent can be determined from the textual representation of user speech. Concepts referred to by the primary user intent can be identified, and substrings of the textual representation of user speech corresponding to the concepts can be identified. Secondary user intents for the substrings can be determined and a task flow based on the primary user intent and the secondary user intents can be generated and performed.

Claims

1. A method for operating a virtual assistant on an electronic device, the method comprising:

receiving a textual representation of user speech;

determining a primary user intent for the textual representation of user speech;

identifying a first type of concept referred to by the primary user intent;

identifying a first substring from the textual representation of user speech corresponding to the first type of concept;

determining a secondary user intent for the first substring; and

performing a task flow comprising one or more tasks based at least in part on the primary user intent for the textual representation of user speech and the secondary user intent for the first substring.

2. The method of claim 1, wherein determining the primary user intent for the textual representation of user speech comprises:

determining a confidence score for a plurality of interpretations of the textual representation of user speech; and

determining the primary user intent for the textual representation of user speech based on an interpretation of the plurality of interpretations of the textual representation of user speech having the highest confidence score.

3. The method of claim 1, wherein the first type of concept comprises a place, a time, an event, or a person.

4. The method of claim 1, wherein identifying the first substring from the textual representation of user speech comprises:

identifying one or more predetermined words corresponding to the first type of concept in the textual representation of user speech; and

identifying the first substring based on the one or more predetermined words corresponding to the first type of concept.

5. The method of claim 1, wherein determining the secondary user intent for the first substring comprises:

determining a confidence score for a plurality of interpretations of the first substring; and

determining the secondary user intent for the first substring based on an interpretation of the plurality of interpretations of the first substring having the highest confidence score.

6. The method of claim 5, wherein the plurality of interpretations of the first substring exclude interpretations from domains that do not output the first type of concept.

7. The method of claim 1, further comprising:

identifying a second type of concept referred to by the primary user intent;

identifying a second substring from the textual representation of user speech corresponding to the second type of concept; and

determining a secondary user intent for the second substring, wherein performing the task flow is further based on the secondary user intent for the second substring.

8. The method of claim 7, wherein the second type of concept comprises a place, a time, an event, or a person.

9. The method of claim 7, wherein identifying the second substring from the textual representation of user speech comprises:

identifying one or more predetermined words corresponding to the second type of concept in the textual representation of user speech; and

identifying the second substring based on the one or more predetermined words corresponding to the second type of concept.

10. The method of claim 7, wherein determining the secondary user intent for the second substring comprises:

determining a confidence score for a plurality of interpretations of the second substring; and

determining the secondary user intent for the second substring based on an interpretation of the plurality of interpretations of the second substring having the highest confidence score.

11. The method of claim 10, wherein the plurality of interpretations of the second substring exclude interpretations from domains that do not output the second type of concept.

12. The method of a claim 7, further comprising:

identifying a third type of concept referred to by the secondary user intent for the first substring;

identifying a third substring from the first substring corresponding to the third type of concept; and

determining a tertiary user intent for the third substring, wherein performing the task flow is further based on the tertiary user intent for the third substring.

13. The method of claim 12, wherein the third type of concept comprises a place, a time, an event, or a person.

14. The method of claim 12, wherein identifying the third substring from the first substring comprises:

identifying one or more predetermined words corresponding to the third type of concept in the first substring; and

identifying the third substring based on the one or more predetermined words corresponding to the third type of concept.

15. The method of claim 12, wherein determining the tertiary user intent for the third substring comprises:

determining a confidence score for a plurality of interpretations of the third substring; and

determining the tertiary user intent for the third substring based on an interpretation of the plurality of interpretations of the third substring having the highest confidence score.

16. The method of claim 15, wherein the plurality of interpretations of the third substring exclude interpretations from domains that do not output the third type of concept.

17. The method of claim 1, wherein performing the task flow comprises:

identifying a primary task flow to accomplish the primary user intent;

identifying one or more constraints associated with the primary task flow;

identifying one or more queries, programs, methods, services, or APIs that satisfy the one or more constraints associated with the primary task flow; and

generating the task flow from the primary task flow and the identified one or more queries, programs, methods, services, or APIs.

18. The method of claim 17, wherein the one or more constraints comprises a type of input required by the primary task flow, and wherein the identified one or more queries, programs, methods, services, or APIs are capable of providing the type of input required by the primary task flow.

19. An electronic device, comprising:

one or more processors;

memory; and

one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for;

receiving a textual representation of user speech;

determining a primary user intent for the textual representation of user speech;

identifying a first type of concept referred to by the primary user intent;

identifying a first substring from the textual representation of user speech corresponding to the first type of concept;

determining a secondary user intent for the first substring; and

performing a task flow comprising one or more tasks based at least in part on the primary user intent for the textual representation of user speech and the secondary user intent for the first substring.

20. The device of claim 19, wherein determining the primary user intent for the textual representation of user speech comprises:

determining a confidence score for a plurality of interpretations of the textual representation of user speech; and

determining the primary user intent for the textual representation of user speech based on an interpretation of the plurality of interpretations of the textual representation of user speech having the highest confidence score.

21. The device of claim 19, wherein the first type of concept comprises a place, a time, an event, or a person.

22. The device of claim 19, wherein identifying the first substring from the textual representation of user speech comprises:

identifying one or more predetermined words corresponding to the first type of concept in the textual representation of user speech; and

identifying the first substring based on the one or more predetermined words corresponding to the first type of concept.

23. The device of claim 19, wherein determining the secondary user intent for the first substring comprises:

determining a confidence score for a plurality of interpretations of the first substring; and

determining the secondary user intent for the first substring based on an interpretation of the plurality of interpretations of the first substring having the highest confidence score.

24. A non-transitory computer-readable storage medium comprising computer-executable instructions for:

receiving a textual representation of user speech;

determining a primary user intent for the textual representation of user speech;

identifying a first type of concept referred to by the primary user intent;

identifying a first substring from the textual representation of user speech corresponding to the first type of concept;

determining a secondary user intent for the first substring; and

performing a task flow comprising one or more tasks based at least in part on the primary user intent for the textual representation of user speech and the secondary user intent for the first substring.