Electronic device using a compound metric for sound enhancement

Patent metadata

Field	Value
Publication number	US-10812915-B2
Application number	US-201816170858-A
Country	US
Kind code	B2
Filing date	Oct 25, 2018
Priority date	Oct 27, 2017
Publication date	Oct 20, 2020
Grant date	Oct 20, 2020

Abstract

A method, comprising receiving at least one sound at an electronic device. The at least one sound is enhanced for the at least one user based on a compound metric. The compound metric is calculated using at least two sound metrics selected from an engineering metric, a perceptual metric, and a physiological metric. The engineering metric comprises a difference between an output signal and a desired signal. At least one of the perceptual metric and the physiological metric is based at least in part on input sensed from the at least one user in response to the received at least one sound.

First claim

What is claimed is:

1. A method, comprising:
receiving at least one sound at an electronic device; and
enhancing the at least one sound for at least one user based on a compound metric, the compound metric calculated using at least two sound metrics selected from an engineering metric, a perceptual metric, and a physiological metric, the engineering metric comprising a difference between an output signal and a desired signal, the perceptual metric and the physiological metric based at least in part on input sensed from the at least one user in response to the received at least one sound.

2. The method of claim 1 , wherein enhancing the at least one sound for the at least one user comprises enhancing the sound using a neural network to enhance the at least one sound for the at least one user.

3. The method of claim 1 , wherein the engineering metric is calculated using a mean squared error (MSE) function of the output signal and the desired signal.

4. The method of claim 1 , wherein the perceptual metric is calculated by using at least one of a short term objective intelligibility metric (STOI), a hearing-aid speech quality index (HASQI), a hearing-aid speech perception index (HASPI), a perceptual evaluation of speech quality (PESQ), and a perceptual evaluation of audio quality (PEAQ).

5. The method of claim 1 , wherein the compound metric is calculated as a cost function.

6. The method of claim 1 , wherein the compound metric is calculated during a predetermined testing time period.

7. The method of claim 6 , wherein the compound metric is calculated at a plurality of time periods subsequent to the predetermined testing time period.

8. The method of claim 1 , wherein the user input comprises one or more of an audible input, a gesture input, and a tactile input.

9. The method of claim 1 , wherein the electronic device is an ear-worn electronic device configured to be worn by the at least one user.

10. The method of claim 1 , wherein the electronic device is a mobile communication device.

11. The method of claim 1 , wherein the at least one sound comprises one or more of speech, music, and an alarm.

12. The method of claim 1 , wherein computing the compound metric comprises building a compound metric model with neural networks using training data.

13. The method of claim 1 , further comprising calculating the compound metric in response to the user input.

14. The method of claim 1 , further comprising calculating the compound metric in response to the difference between the output signal and the clean signal being greater than a predetermined threshold.

15. The method of claim 1 , wherein the physiological metric comprises at least one of an electroencephalogram (EEG) signal, a skin conductance signal, and a heart rate signal.

16. A system, comprising:
an electronic device configured to receive at least one sound;
at least one sensor communicatively coupled to the electronic device, the at least one sensor configured to sense an input from at least one user of the electronic device in response to the received at least one sound; and
a processor communicatively coupled to the electronic device configured to enhance the at least one sound for the at least one user based on a compound metric, the compound metric calculated using at least two sound metrics selected from an engineering metric, a perceptual metric, and a physiological metric, the engineering metric comprising a difference between an output signal and a desired signal.

17. The system of claim 16 , wherein the electronic device is an ear-worn electronic device configured to be worn by the at least one user.

18. The system of claim 16 , wherein the processor is configured to implement a neural network to enhance the at least one sound for the at least one user.

19. The system of claim 16 , wherein the processor is configured to implement at least one of a short term objective intelligibility metric (STOI), a hearing-aid speech quality index (HASQI), a hearing-aid speech perception index (HASPI), a perceptual evaluation of speech quality (PESQ), and a perceptual evaluation of audio quality (PEAQ).

20. The system of claim 16 , wherein the at least one sensor comprises one or more of an electroencephalogram (EEG) sensor, a skin conductance sensor, and a heart rate sensor.

Assignees

• Starkey Labs Inc

Inventors

• Santos Joao F
• Zhang Tao
• Zhao Yan
• Xu Buye
• Giri Ritwik

Classifications

• A61N1/36039

  fitting procedures · CPC title

• H04R25/407

  Circuits for combining signals of a plurality of transducers · CPC title

• H04R25/507

  implemented by neural network or fuzzy logic · CPC title

• G10L25/30

  using neural networks · CPC title

• G10L25/48

  specially adapted for particular use · CPC title