SMART HOME CONNECTED DEVICE CONTEXTUAL LEARNING USING AUDIO COMMANDS

• US 20160225372A1
• Filed: 03/30/2015
• Published: 08/04/2016
• Est. Priority Date: 02/03/2015
• Status: Abandoned Application

• Current Assignee: Samsung Electronics Co. Ltd.
• Original Assignee: Samsung Electronics Co. Ltd.
• Inventors: Cheung, Eric, Markman, Vita, Gava, Fabio
• Application Number:
  US14/672,667
• Publication Number:
  US 20160225372A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06F 3/167 Audio in a user interface, e.g. using voice commands for navigating, audio feedback
• CPC Class Codes: G10L 15/1815 Semantic context, e.g. disambiguation of the recognition hypotheses based on word meaning
• CPC Class Codes: G10L 15/183 using context dependencies, e.g. language models
• 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
• CPC Class Codes: G10L 2015/226 using non-speech characteristics

Abstract

A method includes receiving an audio command by an electronic device to perform an action. Context related to the audio command is learned by one or more other electronic devices connected with the electronic device. One or more other actions are performed by the one or more other electronic devices based on learned context from the audio command received by the electronic device.

Claims

1. A method comprising:

receiving an audio command by an electronic device to perform an action;

learning context related to the audio command by one or more other electronic devices connected with the electronic device; and

performing one or more other actions by the one or more other electronic devices based on learned context from the audio command received by the electronic device.

2. The method of claim 1, further comprising:

processing text information obtained from the audio command for extracting phraselets based on the context.

3. The method of claim 2, further comprising:

expanding the phraselets using language modeling and synonyms.

4. The method of claim 3, wherein the expanding comprises:

selecting a keyword dictionary;

selecting a synonym dictionary based on the selected keyword dictionary;

semantically augmenting a plurality of n-grams based on the selected synonym dictionary;

adding grammatical augments to semantically augmented n-grams; and

generating augmented phrases based on grammatically and semantically augmented n-grams.

5. The method of claim 1, wherein learning context comprises using one or more electronic device sensors for obtaining sensor information for assisting in determining context.

6. The method of claim 5, wherein the one or more electronic device sensors comprise one or more of:

vibration sensor information, temperature sensor information, sound information, humidity information, magnetic field information, proximity information, light information, rotational information, and movement information.

7. The method of claim 1, wherein the other electronic devices use historical information for learning user behavior for action programming based on the learned context.

8. The method of claim 7, wherein the one or more other electronic devices are controlled contextually based on the audio command received by the electronic device.

9. The method of claim 1, wherein the action and the one or more other actions are related based on the learned context.

10. The method of claim 1, wherein the electronic device or the one or more other electronic devices comprise smart product devices.

11. The method of claim 10, wherein the smart product devices comprise an alarm device, a television device, a smart coffee maker, smart electrical outlet controllers, lighting devices, a smart phone device, a tablet device, or a wearable device.

12. An apparatus comprising:

an electronic product device connected with one or more other electronic product devices, the electronic product device is configured to receive an audio command, to interpret the audio command, to perform an action, and to communicate with the one or more other electronic product devices for learning context related to the audio command by the one or more other electronic product devices, wherein the one or more other electronic product devices are configured to perform one or more other actions based on learned context from the audio command received by the electronic product device.

13. The apparatus of claim 12, wherein the electronic product device is further configured to process text information obtained from the audio command for extracting phraselets based on the context.

14. The apparatus of claim 13, wherein the electronic product device is further configured to expand the phraselets using language modeling and synonyms.

15. The apparatus of claim 14, wherein the electronic product device is further configured to expand the phraselets by selecting a keyword dictionary, selecting a synonym dictionary based on the selected keyword dictionary, semantically augmenting a plurality of n-grams based on the selected synonym dictionary, adding grammatical augments to semantically augmented n-grams, and generating augmented phrases based on grammatically and semantically augmented n-grams.

16. The apparatus of claim 12, wherein the one or more other electronic product devices learn context based on using one or more electronic product device sensors for obtaining sensor information used for determining context.

17. The apparatus of claim 16, wherein the sensor information comprises one or more of:

vibration sensor information, temperature sensor information, sound information, humidity information, magnetic field information, proximity information, light information, rotational information, and movement information.

18. The apparatus of claim 12, wherein the one or more other electronic product devices use historical information for learning user behavior for action programming based on the learned context and the audio command.

19. The apparatus of claim 12, wherein the one or more other electronic product devices are controlled contextually based on the audio command received by the electronic product device.

20. The apparatus of claim 12, wherein the action and the one or more other actions are related based on the learned context.

21. The apparatus of claim 12, wherein the electronic product device or the one or more other electronic devices comprise smart product devices.

22. The apparatus of claim 21, wherein the smart product devices comprise an alarm device, a television device, a smart coffee maker, smart electrical outlet controllers, lighting devices, a smart phone device, a tablet device, or a wearable device.

23. An apparatus comprising:

an electronic device coupled with a processor, wherein the electronic device;

provides interactive agent virtualization for potentially solving one or more of common problems and new problems for one or more products using information that is collected from a plurality of agent interactions with a plurality of clients.

24. The apparatus of claim 23, wherein the electronic device communicates with a server device that:

identifies clusters of common problems for the one or more products;

correlates common problems with the one or more products;

discovers the new problems for the one or more products based on mining of the information; and

mines the agent interactions by analyzing and collecting text information from client portions of the agent interactions.

25. The apparatus of claim 24, wherein the server further:

tokenizes the text information;

normalizes text information from tokenized text information;

casts text information using normalized text information;

clusters casted text information based on one or more topics; and

processes clustered casted text information and extracts topic-indicative phraselets for each of the one or more topics.

26. The apparatus of claim 25, wherein the server is configured for expanding the topic-indicative phraselets using language modeling and synonyms, and identifying trending new tokenized text from one or more chat logs stored in the memory.

27. The apparatus of claim 23, wherein said interactive agent virtualization comprises using one or more electronic device sensors for communicating sensor information for assistance in solving one of the one or more common problems and one or more new problems for the one or more products.

28. The apparatus of claim 27, wherein the sensor information comprises one or more of:

vibration sensor information, temperature sensor information, sound information, humidity information, magnetic field information, proximity information, light information, rotational information, and movement information.

29. The apparatus of claim 23, wherein the interactive agent virtualization comprises technician emulation based on interactive communication with a user and the one or more electronic device sensors, and communication between one or more other electronic devices and the server or a cloud-based service.

30. The apparatus of claim 23, wherein the electronic device and the one or more other electronic devices comprise one or more of a television device, a smart phone device, a tablet device, and a wearable device.