Adaptive Vehicle State-Based Hands-Free Phone Noise Reduction With Learning Capability

Patent metadata

Field	Value
Publication number	US-2016019904-A1
Application number	US-201414334627-A
Country	US
Kind code	A1
Filing date	Jul 17, 2014
Priority date	Jul 17, 2014
Publication date	Jan 21, 2016
Grant date	—

Abstract

This disclosure generally relates to a system, apparatus, and method for achieving an adaptive vehicle state-based hands free noise reduction feature. A noise reduction tool is provided for adaptively applying a noise reduction strategy on a sound input that uses feedback speech quality measures and machine learning to develop future noise reduction strategies, where the noise reduction strategies include analyzing vehicle operational state information and external information that are predicted to contribute to cabin noise and selecting noise reducing pre-filter options based on the analysis.

First claim

What is claimed is:

1 . An apparatus, comprising:
a memory configured to store a noise reduction pre-filter and feedback data; a processor in communication with the memory, the processor configured to:
receive a sound input;
receive training input data;
receive the feedback data;
determine whether to select the pre-filter based on the training input data and feedback data, and
if the pre-filter is selected, apply the selected pre-filter to the sound input.

2 . The apparatus of claim 1 , wherein the processor is further configured to:
apply a Weiner filter to the sound input after the selected pre-filter has been applied.

3 . The apparatus of claim 1 , wherein the processor is further configured to:
generate a performance measure on the sound input after the selected pre-filter has been applied, wherein the performance measure indicates a speech quality of the sound input after the selected pre-filter has been applied.

4 . The apparatus of claim 3 , wherein the performance measure is a signal-to-noise measure that identifies an energy level for a speech signal within the sound input after the selected pre-filter has been applied.

5 . The apparatus of claim 3 , wherein the processor is further configured to:
feedback the performance measure as new feedback data, and cause the new feedback data to be stored in the memory.

6 . The apparatus of claim 1 , wherein the training input data includes vehicle operational state information for one or more components of a vehicle that houses the apparatus, and external information, wherein the vehicle operational state information and external information identify factors predicted to contribute, at least in part, to cabin noise within the vehicle.

7 . The apparatus of claim 6 , wherein the vehicle operational state information includes at least one of engine speed information, throttle position information, HVAC mode information, HVAC blower speed information, vehicle speed information, turn signal operational state information, wiper operational state information, car audio volume state information, window position information, spindle acceleration information, cabin acoustics information, cabin microphone position information, and/or seat position information for one or more seats within the vehicle.

8 . The apparatus of claim 6 , wherein the external information includes at least one of geographic information, road surface information, and/or weather information.

9 . The apparatus of claim 6 , further comprising:
an interface configured to:
communicate with an information server;
transmit a request to the information server for the external information, and
in response to the request, receive the external information from the information server.

10 . The apparatus of claim 1 , wherein the selected pre-filter corresponds to one or more available noise reduction pre-filters, and wherein the feedback data is based on a previous noise reduction strategy.

11 . A method for adaptive noise reduction on a sound input, comprising:
storing, in a memory, a noise reduction pre-filter and feedback data; receiving the sound input; receiving training input data; receiving the feedback data; determining whether to select the pre-filter based on the training input data and feedback data, and if the pre-filter is selected, applying the selected pre-filter to the sound input.

12 . The method of claim 11 , further comprising:
applying a Weiner filter to the sound input after the selected pre-filter has been applied.

13 . The method of claim 11 , further comprising:
generating a performance measure on the sound input after the selected pre-filter has been applied, wherein the performance measure indicates a speech quality of the sound input after the selected pre-filter has been applied.

14 . The method of claim 13 , wherein the performance measure is a signal-to-noise measure that identifies an energy level for a speech signal within the sound input after the selected pre-filter has been applied.

15 . The method of claim 13 , further comprising:
feeding back the performance measure as new feedback data, and causing the new feedback data to be stored in the memory.

16 . The method of claim 11 , wherein the training input data includes vehicle operational state information for one or more components of a vehicle, and external information, wherein the vehicle operational state information and external information identify factors predicted to contribute, at least in part, to cabin noise within the vehicle.

17 . The method of claim 16 , wherein the vehicle operational state information includes at least one of engine speed information, throttle position information, HVAC mode information, HVAC blower speed information, vehicle speed information, turn signal operational state information, wiper operational state information, car audio volume state information, window position information, spindle acceleration information, cabin acoustics information, cabin microphone position information, and/or seat position information for one or more seats within the vehicle.

18 . The method of claim 16 , wherein the external information includes at least one of geographic information, road surface information, and/or weather information.

19 . The method of claim 16 , further comprising:
causing an interface to communicate with an information server; transmitting a request to the information server for the external information, and in response to the request, receiving the external information from the information server.

20 . The method of claim 11 , wherein the selected pre-filter corresponds to one or more available noise reduction pre-filters, and wherein the feedback data is based on a previous noise reduction strategy.

Assignees

• Ford Global Tech Llc

Inventors

• Charette Francois
• Cooprider Anthony Dwayne
• Nicastri Paul J Joseph
• Gur Yuksel
• Amman Scott Andrew
• Puskorius Gintaras Vincent

Classifications

• G10L25/48

  specially adapted for particular use · CPC title

• H04M1/6075

  adapted for handsfree use in a vehicle (H04M1/6058 takes precedence; arrangements for holding telephones in a vehicle B60R11/0241) · CPC title

• G10L2021/02085

  Periodic noise · CPC title

• G10L21/0208 Primary

  Noise filtering · CPC title

• G10L25/60

  for measuring the quality of voice signals · CPC title