METHOD FOR EXTRACTING SALIENT DIALOG USAGE FROM LIVE DATA

• US 20150161521A1
• Filed: 12/06/2013
• Published: 06/11/2015
• Est. Priority Date: 12/06/2013
• Status: Active Grant

• Current Assignee: Apple Inc.
• Original Assignee: Apple Inc.
• Inventors: SHAH, Rushin N., NAIK, Devang K.
• Granted Patent: US 10,296,160 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 3/0481 based on specific properties of the displayed interaction object or a metaphor-based environment, e.g. interaction with desktop elements like windows or icons, or assisted by a cursor's changing behaviour or appearance
• CPC Class Codes: G06F 40/295 Named entity recognition
• CPC Class Codes: G06N 20/00 Machine learning

Abstract

Systems and processes are disclosed for virtual assistant request recognition using live usage data and data relating to future events. User requests that are received but not recognized can be used to generate candidate request templates. A count can be associated with each candidate request template and can be incremented each time a matching candidate request template is received. When a count reaches a threshold level, the corresponding candidate request template can be used to train a virtual assistant to recognize and respond to similar user requests in the future. In addition, data relating to future events can be mined to extract relevant information that can be used to populate both recognized user request templates and candidate user request templates. Populated user request templates (e.g., whole expected utterances) can then be used to recognize user requests and disambiguate user intent as future events become relevant.

Claims

1. A method for request recognition for a virtual assistant, the method comprising:

receiving a textual representation of user speech;

generating a plurality of request templates based on the textual representation;

associating a count with a request template of the plurality of request templates based on a number of times the request template is received; and

in response to a determination that the count is more than a predetermined amount, generating a notification including the request template.

2. The method of claim 1, further comprising:

in response to a determination that the count is more than the predetermined amount, training a language model with the request template, the language model associated with the virtual assistant.

3. The method of claim 1, further comprising:

in response to a determination that the count is more than the predetermined amount, generating a plurality of populated templates, each of the plurality of populated templates comprising one of the plurality of generated request templates populated with an entity.

4. The method of claim 3, further comprising:

training a language model with the plurality of populated templates.

5. The method of claim 1, wherein each of the generated plurality of request templates comprises at least one word or phrase that indicates a language domain and at least one entity related to the language domain.

6. The method of claim 1, further comprising:

receiving contextual data relating to the textual representation of user speech;

wherein the plurality of request templates is generated based on the textual representation and the contextual data relating to the textual representation.

7. A system for request recognition for a virtual assistant, the system comprising:

a memory; and

a processor capable of;

receiving a textual representation of user speech;

generating a plurality of request templates based on the textual representation;

associating a count with a request template of the plurality of request templates based on a number of times the request template is received; and

in response to a determination that the count is more than a predetermined amount, generating a notification including the request template.

8. A method for facilitating user interactions with a virtual assistant associated with a user device, the method comprising:

receiving a first user query at the user device;

providing a response indicating that the virtual assistant is untrained to respond to the first user query;

transmitting the first user query to a server associated with the virtual assistant;

receiving a second user query at the user device, wherein the second user query is the same as the first user query; and

in response to receiving the second user query, providing a trained response.

9. The method of claim 8, wherein the trained response is determined by:

generating a plurality of request templates based on the first user query;

associating a count with a request template of the plurality of request templates based on a number of times the request template is received; and

in response to a determination that the count is more than a predetermined amount, generating the trained response.

10. The method of claim 8, wherein the trained response comprises a search result associated with the second user query.

11. A method for request recognition for a virtual assistant, the method comprising:

receiving data comprising a reference to a future event;

extracting an entity name from the received data, wherein the entity name describes the future event;

generating a plurality of populated request templates based on the extracted entity name; and

training a language model of the virtual assistant with the plurality of populated request templates.

12. The method of claim 11, wherein generating the plurality of populated request templates based on the extracted entity name comprises:

inserting the extracted entity name into a plurality of request templates recognizable by the virtual assistant.

13. The method of claim 11, further comprising:

inserting the extracted entity name into a first request template recognizable by the virtual assistant;

receiving a second request template as yet unrecognized by the virtual assistant; and

generating a candidate populated request template based on the extracted entity name by inserting the extracted entity name into the second request template.

14. The method of claim 13, further comprising:

training the language model of the virtual assistant with the candidate populated request template.

15. A method for request recognition for a virtual assistant, the method comprising:

receiving a textual transcription of user speech;

comparing the textual transcription to one or more first request templates recognizable by the virtual assistant;

in response to a first match between the textual transcription and the first request template being found, causing an action to be performed corresponding to the first match; and

in response to no first match being found;

generating a plurality of second request templates based on the textual transcription;

comparing each of the plurality of second request templates to one or more third request templates as yet unrecognized by the virtual assistant;

incrementing a count associated with a second request template in response to a second match between the second request template and a third request template being found; and

storing a second request template in response to a matching third request template not being found.

16. The method of claim 15, further comprising:

in response to a determination that the incremented count is more than a predetermined threshold, generating a notification including the second request template.

17. The method of claim 15, further comprising:

in response to no first match being found, training a language model with at least one of the plurality of generated second request templates.

18. The method of claim 15, further comprising:

in response to no first match being found, generating a plurality of populated request templates, each of the plurality of populated request templates comprising one of the plurality of generated second request templates populated with an entity; and

training a language model with the plurality of populated request templates.

19. The method of claim 15, wherein the action to be performed comprises causing a search result associated with the first match to be displayed.

20. The method of claim 15, wherein each of the plurality of second request templates comprises at least one word or phrase that indicates a language domain.

21. The method of claim 15, further comprising:

receiving contextual data relating to the textual transcription of user speech;

wherein the plurality of second request templates is generated based on the textual transcription and the contextual data relating to the textual transcription.

22. A system for request recognition for a virtual assistant, the system comprising:

a memory; and

a processor capable of;

receiving a textual transcription of user speech;

comparing the textual transcription to one or more first request templates recognizable by the virtual assistant;

in response to a first match between the textual transcription and the first request template being found, causing an action to be performed corresponding to the first match; and

in response to no first match being found;

generating a plurality of second request templates based on the textual transcription;

comparing each of the plurality of second request templates to one or more third request templates as yet unrecognized by the virtual assistant;

incrementing a count associated with a second request template in response to a second match between the second request template and a third request template being found; and

storing a second request template in response to a matching third request template not being found.

23. The system of claim 22, the processor further capable of:

in response to a determination that the incremented count is more than a predetermined threshold, generating a notification including the second request template.

24. The system of claim 22, the processor further capable of:

in response to no first match being found, training a language model with at least one of the plurality of generated second request templates.

25. The system of claim 22, the processor further capable of:

in response to no first match being found, generating a plurality of populated request templates, each of the plurality of populated request templates comprising one of the plurality of generated second request templates populated with an entity; and

training a language model with the plurality of populated request templates.