System and Method for Performing Voice Activity Detection

• US 20130294614A1
• Filed: 05/01/2012
• Published: 11/07/2013
• Est. Priority Date: 05/01/2012
• Status: Active Grant

• Current Assignee: Audyssey Laboratories, Inc.
• Original Assignee: Audyssey Laboratories, Inc.
• Inventors: Bharitkar, Sunil, Dahlin, Nathan
• Granted Patent: US 9,002,030 B2
• Time in Patent Office: Days
• US Class Current: 381/71.1
• CPC Class Codes: G10L 2025/786 Adaptive threshold
• CPC Class Codes: G10L 21/0232 Processing in the frequency domain
• CPC Class Codes: G10L 25/78 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 Class Codes: H04M 9/082 using echo cancellers echo cancellers per se H04B3/23

Abstract

A Voice Activity Detection (VAD) algorithm provides a simple binary signal indicating the presence or absence of speech in a microphone signal. The VAD algorithm includes a first step of noise suppression which both estimates and removes (i.e., filters) ambient noise from the microphone signal to create a filtered signal. The magnitude of the filtered signal is then compared to a threshold in order to produce a VAD output signal. The threshold is dynamic and may be derived either from the filtered signal itself, or from a noise spectrum estimate calculated by the noise suppression step.

Claims

1. A method for Voice Activity Detection (VAD), the method comprising the steps of:

producing a microphone signal including speech and ambient noise by a microphone;

providing the microphone signal to noise suppression processing;

processing the microphone signal in the noise suppression processing to generate an ambient noise estimate;

providing the ambient noise estimate to threshold calculation;

calculating a threshold;

provided the threshold to the VAD logic;

computing a noise suppressed signal from the microphone signal and the ambient noise estimate by the noise suppression processing;

comparing the noise suppressed signal to a threshold in the VAD logic;

setting a VAD signal to 0 when the noise suppressed signal is below the threshold; and

setting a VAD signal to 1 when the noise suppressed signal is above the

6. The method of claim 1, wherein processing the microphone signal in the noise suppression processing to generate an ambient noise estimate comprises:

buffering and windowing the microphone signal to create time domain frames;

sequentially transforming the time domain frames into microphone signal frequency domain frames; and

computing frequency domain noise estimate frames of each of the microphone signal frequency domain frames;

7. The method of claim 6, wherein computing a noise suppressed signal comprises:

calculating trims from the frequency domain noise estimate frames; and

scaling the microphone signal frequency domain frames using the trims to obtain the noise suppressed signal.

8. The method of claim 7, further including calculating a signal energy estimate as the square of the magnitude of noise suppressed signal.

9. The method of claim 8, wherein comparing the noise suppressed signal to a threshold in the VAD logic comprises comparing the current signal energy estimate to a threshold determined by prior signal energy estimates.

10. The method of claim 9, wherein the threshold is determined by:

during the most recent non-speech frames, setting the threshold to the scaled result of a first order smoother applied to the prior signal energy estimates.

2. The method of claim 1, wherein processing the microphone signal in the noise suppression processing to generate an ambient noise estimate comprises:

buffering and windowing the microphone signal to create time domain frames;

transforming the time domain frames into frequency domain frame; and

computing noise estimates of each of the frequency domain frames.

3. The method of claim 2, wherein computing a noise suppressed signal comprises:

computing trim values from the noise estimates; and

scaling the frequency domain frame by the trim values.

4. The method of claim 3, further including calculating the threshold as the square root and mean of the noise estimates.

5. The method of claim 4, wherein calculating trims from the frequency domain noise estimate frames includes using over subtraction factor and a noise floor factor to limit the trims.

11. The method of claim 10, wherein calculating trims from the frequency domain noise estimate frames includes using over subtraction factor and a noise floor factor to limit the trims.

10-1. A method for Voice Activity Detection (VAD), the method comprising the steps of:

producing a microphone signal including speech and ambient noise by a microphone;

buffering and windowing the microphone signal to create time domain frames;

sequentially transforming the time domain frames into microphone signal frequency domain frames;

computing frequency domain noise estimate frames of each of the microphone signal frequency domain frames;

calculating trims from the frequency domain noise estimate frames;

scaling the microphone signal frequency domain frames using the trims to obtain a frequency domain noise suppressed signal;

inverse transforming the frequency domain noise suppressed signal into a time domain noise suppressed signal;

buffering and windowing the time domain noise suppressed signal;

squaring the buffered and windowed time domain noise suppressed signal to generate a signal energy estimate;

determining a threshold using prior signal energy estimate;

comparing the present signal energy estimate to the threshold in the VAD logic;

setting a VAD signal to 0 when the signal energy estimate is below the threshold; and

setting a VAD signal to 1 when the signal energy estimate is above the threshold.

11-2. The method of claim 10, wherein the VAD signal is held to “

0”

during a threshold initialization period.

12. A method for Voice Activity Detection (VAD), the method comprising the steps of:

producing a microphone signal including speech and ambient noise by a microphone;

buffering and windowing the microphone signal to create time domain frames;

sequentially transforming the time domain frames into microphone signal frequency domain frames;

computing frequency domain ambient noise estimate frames of each of the microphone signal frequency domain frames;

providing the frequency domain ambient noise estimate to threshold calculation;

calculating a threshold by taking the square root of each bin of the frequency domain noise estimate frames and then taking the mean of the square roots of each bins;

provided the threshold to the VAD logic;

calculating trims from the frequency domain noise estimate frames;

scaling the microphone signal frequency domain frames using the trims to obtain a frequency domain noise suppressed signal;

inverse transforming the frequency domain noise suppressed signal into a time domain noise suppressed signal;

buffering and windowing the time domain noise suppressed signal;

provided the buffered and windowed time domain noise suppressed signal to the VAD logic;

comparing the buffered and windowed time domain noise suppressed signal to a threshold in the VAD logic;

setting a VAD signal to 0 when the windowed time domain noise suppressed signal is below the threshold; and

setting a VAD signal to 1 when the windowed time domain noise suppressed signal is above the threshold.