SYSTEM FOR SPEECH KEYWORD DETECTION AND ASSOCIATED METHOD

• US 20150161989A1
• Filed: 01/29/2014
• Published: 06/11/2015
• Est. Priority Date: 12/09/2013
• Status: Active Grant

• Current Assignee: MediaTek, Inc.
• Original Assignee: MediaTek, Inc.
• Inventors: Hsu, Chao-Ling, Cheng, Yiou-Wen, Sun, Liang-Che, Wang, Yuanyuan
• Granted Patent: US 9,747,894 B2
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G10L 15/08 Speech classification or search
• CPC Class Codes: G10L 15/22 Procedures used during a speech recognition process, e.g. man-machine dialogue
• CPC Class Codes: G10L 2015/228 of application context

Abstract

The invention provides a system for speech keyword detection and associated method. The system includes a speech keyword detector, an activity predictor and a decision maker. The activity predictor obtains sensor data provided by a plurality of sensors, and processes the sensor data to provide an activity prediction result indicating a probability for whether a user is about to give voice keyword. The decision maker processes the activity prediction result and a preliminary keyword detection result of the speech keyword detection to provide a keyword detection result.

Claims

1. A system for speech keyword detection of a device, comprising:

an activity predictor capable of obtaining sensor data provided by a plurality of sensors, and capable of processing the sensor data to provide an activity prediction result indicating a probability for whether a user is about to give a voice keyword;

a speech keyword detector for generating a preliminary keyword detection result; and

a decision maker coupled to the activity predictor and the speech keyword detector, and capable of processing the activity prediction result and the preliminary keyword detection result to provide a keyword detection result.

2. The system of claim 1 further comprising:

an activity database comprising a plurality of activity lists;

each activity list being associated with a target application, and comprising a plurality of activity templates,

wherein the activity predictor is capable of;

obtaining a selected one of the activity lists, wherein the target application associated with the selected activity list matches a currently running application of the device; and

comparing the sensor data with each activity template of the selected activity list to provide the activity prediction result.

3. The system of claim 1 further comprising:

an activity database comprising a plurality of activity lists;

each activity list being associated with a target application, and comprising a plurality of activity templates,

wherein the activity predictor is capable of;

obtaining a selected one of the activity lists, wherein the target application associated with the selected activity list matches a currently running application of the device;

providing extracted data by extracting features of the sensor data; and

comparing the extracted data with each activity template of the selected activity list to provide the activity prediction result.

4. The system of claim 1 further comprising:

a keyword database comprising a plurality of keyword lists;

each keyword list being associated with a target application, and comprising a plurality of candidate keywords,

wherein the speech keyword detector is capable of;

obtaining a selected one of the keyword lists, wherein the target application associated with the selected keyword list matches a currently running application of the device; and

comparing incoming sound with each candidate keyword of the selected keyword list to provide the preliminary keyword detection result.

5. The system of claim 1 further comprising:

a voice detector capable of evaluating informativeness of the incoming sound to selectively enable the speech keyword detector.

6. The system of claim 5, wherein the voice detector comprises:

a first estimator capable of computing a current sample of a first sequence as a weighted sum of a current volume of the incoming sound and a preceding sample of the first sequence;

a second estimator capable of computing a current sample of a second sequence as a weighted sum of a current volume of the incoming sound and a preceding sample of the second sequence; and

a comparator, coupled to the first estimator and the second estimator, comparing the first sequence and the second sequence to indicate the informativeness of the incoming sound.

7. The system of claim 5, wherein the voice detector comprises:

a first estimator capable of computing a current sample of a first sequence by summing a first product and a second product, the first product multiplying a preceding sample of the first sequence with a first weighting, and the second product multiplying a current volume of incoming sound with a first complementary weighting;

a second estimator capable of computing a current sample of a second sequence by summing a third product and a fourth product, the third product multiplying a preceding sample of the second sequence with a second weighting, and the fourth product multiplying a current volume of incoming sound with a second complementary weighting; and

a comparator, coupled to the first estimator and the second estimator, comparing the first sequence and the second sequence to indicate the informativeness of incoming sound.

8. The system of claim 7, wherein the first weighting is less than the second weighting.

9. The system of claim 1, wherein the decision maker applies a probability fusion algorithm to process the activity prediction result and the preliminary keyword detection result for providing the keyword detection result.

10. The system of claim 1, wherein the decision maker is capable of adopting a machine learning algorithm to process the activity prediction result and the preliminary keyword detection result for proving the keyword detection result.

11. The system of claim 1, wherein the decision maker calculates a linear combination of the activity prediction result and the preliminary keyword detection result as the keyword detection result.

12. The system of claim 1, wherein the sensors include at least one of the following:

an accelerometer, a gyroscope, a magnetometer, a barometer, a proximity sensor, a light sensor, a touch screen, a receiver of a positioning system, a wireless receiver and a camera.

13. A method for speech keyword detection, comprising:

obtaining sensor data provided by a plurality of sensors;

according to the sensor data, computing an activity prediction result indicating a probability for whether a user is about to give voice keyword; and

computing a keyword detection result according to the activity prediction result and a preliminary keyword detection result of the speech keyword detection.

14. The method of claim 13 further comprising:

providing an activity database which comprises a plurality of activity lists;

each activity list being associated with a target application, and comprising a plurality of activity templates;

identifying currently running application of the device;

selecting one of the activity lists by comparing the currently running application with each target application of each activity list; and

comparing the sensor data with each activity template of the selected activity list to provide the activity prediction result.

15. The method of claim 13 further comprising:

providing an activity database which comprises a plurality of activity lists;

each activity list being associated with a target application, and comprising a plurality of activity templates;

identifying currently running application of the device;

by comparing the currently running application with each target application of each activity list, selecting one of the activity lists;

providing extracted data by extracting features of the sensor data;

comparing the extracted data with each activity template of the selected activity list and accordingly providing an activity matching result to be included in the activity prediction result.

16. The method of claim 13 further comprising:

providing a keyword database which comprises a plurality of keyword lists;

each keyword list being associated with a target application, and comprising a plurality of candidate keywords;

identifying currently running application of the device;

selecting one of the keyword lists by comparing the currently running application with each target application of each keyword list; and

providing the preliminary keyword detection result by comparing incoming sound with each candidate keyword of the selected keyword list.

17. The method of claim 13 further comprising:

performing a voice detection by evaluating informativeness of incoming sound to selectively enable the speech keyword detection.

18. The method of claim 17, wherein the step of performing the voice detection comprises:

computing a current sample of a first sequence as a weighted sum of a current volume of incoming sound and a preceding sample of the first sequence;

computing a current sample of a second sequence as a weighted sum of a current volume of incoming sound and a preceding sample of the second sequence; and

comparing the first sequence and the second sequence to indicate the informativeness of incoming sound.

19. The method of claim 17, wherein the step of performing the voice detection comprises:

computing a current sample of a first sequence by summing a first product and a second product, the first product multiplying a preceding sample of the first sequence with a first weighting, and the second product multiplying a current volume of incoming sound with a first complementary weighting;

computing a current sample of a second sequence by summing a third product and a fourth product, the third product multiplying a preceding sample of the second sequence with a second weighting, and the fourth product multiplying a current volume of incoming sound with a second complementary weighting; and

comparing the current sample of the first sequence and the current sample of the second sequence to indicate the informativeness of incoming sound.

20. The method of claim 19, wherein the first weighting is less than the second weighting.

21. The method of claim 13, wherein computing the keyword detection result comprises:

adopting a probability fusion algorithm to process the activity prediction result and the preliminary keyword detection result.

22. The method of claim 13, wherein computing the keyword detection result comprises:

adopting a machine learning algorithm to process the activity prediction result and the preliminary keyword detection result.

23. The method of claim 13, wherein the step of computing the keyword detection result calculates a linear combination of activity prediction result and the preliminary keyword detection result as the keyword detection result.

24. The method of claim 13, wherein the sensors includes at least one of the following:

an accelerometer, a gyroscope, a magnetometer, a barometer, a proximity sensor, a light sensor, a touch screen, a receiver of a positioning system, a wireless receiver and a camera.