Voice activity detection (VAD) devices and methods for use with noise suppression systems

• US 20030179888A1
• Filed: 03/05/2003
• Published: 09/25/2003
• Est. Priority Date: 03/05/2002
• Status: Abandoned Application

• Current Assignee: JAWB Acquisition LLC
• Original Assignee: JAWB Acquisition LLC
• Inventors: Asseily, Alexander M., Petit, Nicolas J., Burnett, Gregory C., Einaudi, Andrew E.
• Application Number:
  US10/383,162
• Publication Number:
  US 20030179888A1
• Time in Patent Office: Days
• US Class Current: 381/71.8
• CPC Class Codes: G10L 2021/02165 Two microphones, one receiving mainly the noise signal and the other one mainly the speech signal
• CPC Class Codes: G10L 2025/783 based on threshold decision
• CPC Class Codes: G10L 21/0208 Noise filtering

Abstract

Voice Activity Detection (VAD) devices, systems and methods are described for use with signal processing systems to denoise acoustic signals. Components of a signal processing system and/or VAD system receive acoustic signals and voice activity signals. Control signals are automatically generated from data of the voice activity signals. Components of the signal processing system and/or VAD system use the control signals to automatically select a denoising method appropriate to data of frequency subbands of the acoustic signals. The selected denoising method is applied to the acoustic signals to generate denoised acoustic signals.

Claims

1. A system for denoising acoustic signals, comprising:

a denoising subsystem including at least one receiver coupled to provide acoustic signals of an environment to components of the denoising subsystem;

a voice detection subsystem coupled to the denoising subsystem, the voice detection subsystem receiving voice activity signals that include information of human voicing activity, wherein components of the voice detection subsystem automatically generate control signals using information of the voice activity signals,

wherein components of the denoising subsystem automatically select at least one denoising method appropriate to data of at least one frequency subband of the acoustic signals using the control signals; and

wherein components of the denoising subsystem process the acoustic signals using the selected denoising method to generate denoised acoustic signals.

2. The system of claim 1, wherein the receiver couples to at least one microphone array that detects the acoustic signals.

3. The system of claim 2, wherein the microphone array includes at least two closely-spaced microphones.

4. The system of claim 1, wherein the voice detection subsystem receives the voice activity signals via a sensor, wherein the sensor is selected from among at least one of an accelerometer, a skin surface microphone in physical contact with skin of a user, a human tissue vibration detector, a radio frequency (RF) vibration detector, a laser vibration detector, an electroglottograph (EGG) device, and a computer vision tissue vibration detector.

5. The system of claim 1, wherein the voice detection subsystem receives the voice activity signals via a microphone array coupled to the receiver, the microphone array including at least one of a microphone, a gradient microphone, and a pair of unidirectional microphones.

6. The system of claim 1, wherein the voice detection subsystem receives the voice activity signals via a microphone array coupled to the receiver, wherein the microphone array includes a first unidirectional microphone co-located with a second unidirectional microphone, wherein the first unidirectional microphone is oriented so that a spatial response curve maximum of the first unidirectional microphone is approximately in a range of 45 to 180 degrees in azimuth from a spatial response curve maximum of the second unidirectional microphone.

7. The system of claim 1, wherein the voice detection subsystem receives the voice activity signals via a microphone array coupled to the receiver, wherein the microphone array includes a first unidirectional microphone positioned colinearly with a second unidirectional microphone.

8. A method for denoising acoustic signals, comprising:

receiving acoustic signals and voice activity signals;

automatically generating control signals from data of the voice activity signals;

automatically selecting at least one denoising method appropriate to data of at least one frequency subband of the acoustic signals using the control signals; and

applying the selected denoising method and generating the denoised acoustic signals.

9. The method of claim 8, wherein selecting further comprises selecting a first denoising method for frequency subbands that include voiced speech.

10. The method of claim 9, wherein selecting further comprises selecting a second denoising method for frequency subbands that include unvoiced speech.

11. The method of claim 8, wherein selecting further comprises selecting a denoising method for frequency subbands devoid of speech.

12. The method of claim 8, wherein selecting further comprises selecting a denoising method in response to noise information of the received acoustic signal, wherein the noise information includes at least one of noise amplitude, noise type, and noise orientation relative to a speaker.

13. The method of claim 8, wherein selecting further comprises selecting a denoising method in response to noise information of the received acoustic signal, wherein the noise information includes noise source motion relative to a speaker.

14. A method for removing noise from acoustic signals, comprising:

receiving acoustic signals;

receiving information associated with human voicing activity;

generating at least one control signal for use in controlling removal of noise from the acoustic signals;

in response to the control signal, automatically generating at least one transfer function for use in processing the acoustic signals in at least one frequency subband;

applying the generated transfer function to the acoustic signals; and

removing noise from the acoustic signals.

15. The method of claim 14, further comprising dividing the received acoustic signals into a plurality of frequency subbands.

16. The method of claim 14, wherein generating the transfer function further comprises adapting coefficients of at least one first transfer function representative of the acoustic signals of a subband when the control signal indicates that voicing information is absent from the acoustic signals of a subband.

17. The method of claim 14, wherein generating the transfer funcation further comprises generating at least one second transfer function representative of the acoustic signals of a subband when the control signal indicates that voicing information is present in the acoustic signals of a subband.

18. The method of claim 14, wherein applying the generated transfer function further comprises:

generating a noise waveform estimate associated with noise of the acoustic signals; and

subtracting the noise waveform estimate from the acoustic signal when the acoustic signal includes speech and noise.