Detection of loudspeaker playback

Patent metadata

Field	Value
Publication number	US-10616701-B2
Application number	US-201816189372-A
Country	US
Kind code	B2
Filing date	Nov 13, 2018
Priority date	Nov 14, 2017
Publication date	Apr 7, 2020
Grant date	Apr 7, 2020

Abstract

A method of determining whether a sound has been generated by a loudspeaker comprises receiving an audio signal representing at least a part of the sound. The audio signal is separated into different frequency bands. The signal content of different frequency bands are compared. Based on said comparison, frequency-based variations in signal content indicative of use of a loudspeaker are identified.

First claim

The invention claimed is:

1. A method of determining whether a sound has been generated by a loudspeaker, the method comprising:
receiving an audio signal representing at least a part of the sound;
separating the received audio signal into a first audio frequency component containing first audio frequencies and a second audio frequency component containing second audio frequencies;
obtaining a first statistical metric relating to sample values of the first audio frequency component and obtaining a second statistical metric relating to sample values of the second audio frequency component; and
based on said first statistical metric and said second statistical metric, determining whether said sound is indicative of use of a loudspeaker by detecting features resulting from a non-linearity that is greater at said first audio frequencies than at said second audio frequencies.

2. A method according to claim 1 , further comprising:
if said features indicative of use of a loudspeaker are identified, generating a loudspeaker indication output signal.

3. A method according to claim 1 , wherein at least one of the first statistical metric and the second statistical metric is a measure of an asymmetry of a waveform of the sound.

4. A method according to claim 1 , wherein at least one of the first statistical metric and the second statistical metric is a measure of skew of the sample values.

5. A method according to claim 1 , comprising:
obtaining a measure of skew of sample values of the first audio frequency component;
obtaining a measure of skew of sample values of the second audio frequency component; and
determining that the received audio signal has features resulting from a non-linearity that is greater at first audio frequencies than at second audio frequencies, if a difference between the measure of skew of sample values of the first audio frequency component and the measure of skew of sample values of the second audio frequency component exceeds a threshold value.

6. A method according to claim 1 , wherein obtaining the first statistical metric and obtaining the second statistical metric relating to sample values of the respective component comprises obtaining a first Cumulative Distribution Function relating to sample values of the first component and obtaining a second Cumulative Distribution Function relating to sample values of the second component.

7. A method according to claim 6 , wherein attempting to detect features resulting from a non-linearity that is greater at said first audio frequencies than at said second audio frequencies comprises:
comparing each Cumulative Distribution Function with a respective reference Cumulative Distribution Function for the respective component to obtain a measure of a difference therebetween; and
comparing said measures of difference obtained for the respective components.

8. A method according to claim 6 , wherein comparing signal content of different frequency bands comprises comparing the Cumulative Distribution Functions relating to the respective components.

9. A method according to claim 1 , comprising using a machine learning technique to attempt to detect in the received audio signal the features resulting from a non-linearity that is greater at low audio frequencies than at high audio frequencies.

10. A method according to claim 1 , comprising:
receiving a first signal representing the sound;
deriving from the first signal a second signal representing a part of the sound; and
attempting to detect in the second signal the features resulting from a non-linearity that is greater at first audio frequencies than at second audio frequencies.

11. A method according to claim 10 , wherein the second signal represents speech.

12. A method according to claim 11 , wherein the second signal represents voiced speech.

13. A method according to claim 10 , comprising:
receiving the first signal at a voice activity detector; and
deriving the second signal representing speech only if the voice activity detector detects speech in the first signal.

14. A method according to claim 1 , for use in a voice biometrics system, further comprising:
determining that the sound may result from a replay attack on the voice biometrics system, if it is determined that the sound was generated by a loudspeaker.

15. A system for determining whether a sound has been generated by a loudspeaker, the system comprising an input for receiving an audio signal representing at least a part of the sound; and a processor, and the system being configured for:
receiving the audio signal representing at least a part of the sound;
separating the received audio signal into a first audio frequency component containing first audio frequencies and a second audio frequency component containing second audio frequencies;
obtaining a first statistical metric relating to sample values of the first audio frequency component and obtaining a second statistical metric relating to sample values of the second audio frequency component; and
based on said first statistical metric and said second statistical metric, determining whether said sound is indicative of use of a loudspeaker by detecting features resulting from a non-linearity that is greater at said first audio frequencies than at said second audio frequencies.

16. A computer program product, comprising a non-transitory computer-readable medium having stored thereon instructions, the instructions, when read and executed by a processor, for performing a method of determining whether a sound has been generated by a loudspeaker, the method comprising:
receiving an audio signal representing at least a part of the sound;
separating the received audio signal into a first audio frequency component containing first audio frequencies and a second audio frequency component containing second audio frequencies;
obtaining a first statistical metric relating to sample values of the first audio frequency component and obtaining a second statistical metric relating to sample values of the second audio frequency component; and
based on said first statistical metric and said second statistical metric, determining whether said sound is indicative of use of a loudspeaker by detecting features resulting from a non-linearity that is greater at said first audio frequencies than at said second audio frequencies.

Assignees

• Cirrus Logic Int Semiconductor Ltd
• Cirrus Logic Inc

Inventors

• Lesso John Paul

Classifications

• G10L25/51

  for comparison or discrimination · CPC title

• H04R2430/03

  Synergistic effects of band splitting and sub-band processing · CPC title

• H04R29/001 Primary

  for loudspeakers (H04R29/007 takes precedence) · CPC title

• G10L25/78

  Detection of presence or absence of voice signals (switching of direction of transmission by voice frequency in two-way loud-speaking telephone systems H04M9/10) · CPC title

• G06F21/32

  using biometric data, e.g. fingerprints, iris scans or voiceprints · CPC title