Single channel suppression of impulsive interferences in noisy speech signals
View Patent ↗Methods and apparatus for reducing impulsive interferences in a signal, without necessarily ascertaining a pitch frequency in the signal, detect onsets of the impulsive interferences by searching a spectrum of high-energy components for large temporal derivatives that are correlated along frequency and extend from a very low frequency up, possibly to about several kHz. The energies of the impulsive interferences are estimated, and these estimates are used to suppress the impulsive interferences. Optionally, techniques are employed to protect desired speech signals from being corrupted as a result of the suppression of the impulsive interferences.
1. A method for reducing impulsive interferences in a noisy speech signal, the method comprising:
receiving the noisy speech signal from a microphone of a device;
identifying, using a computer processor of the device, a plurality of high-energy components of the noisy speech signal, wherein energy of each of the plurality of identified high-energy components exceeds a predetermined threshold;
identifying, using one or more computer processors of the device, a plurality of temporal derivatives for each of the plurality of identified high-energy components, wherein each of the temporal derivatives comprise changes over time in energies of a respective frequency component, wherein each of the plurality of identified temporal derivatives is associated with a respective frequency range, and the frequency ranges associated with the plurality of identified temporal derivatives collectively form a contiguous range of frequencies beginning below a predetermined frequency;
morphologically filtering, using the one or more computer processors of the device, the identified plurality of temporal derivatives, including detecting onsets of the impulsive interferences and estimating a plurality of interference energies in the noisy speech signal, based at least in part on the plurality of identified temporal derivatives, wherein the impulsive interferences correspond to bursts of energy in the noisy speech signal having a substantially random time of occurrence; and
suppressing, using the one or more computer processors of the device, portions of the noisy speech signal having the impulsive interferences, based on the plurality of estimated interference energies to generate an enhanced speech signal for automatic speech recognition.
2. A method according to claim 1 , wherein identifying the plurality of high-energy components comprises determining the threshold, such that the threshold is below a spectral envelope of the signal.
3. A method according to claim 1 , wherein identifying the plurality of high-energy components comprises determining the threshold, based at least in part on a spectral envelope of the signal and at least in part on a power spectral density of stationary noise in the signal.
4. A method according to claim 3 , wherein determining the threshold comprises determining the threshold, such that:
under a first condition, the threshold is a calculated value below the spectral envelope of the signal; and
under a second condition, the threshold is a calculated value above the power spectral density of the stationary noise.
5. A method according to claim 1 , wherein the contiguous range of frequencies is a semi-contiguous range of frequencies comprising at least one gap, wherein each gap of the at least one gap is less than a predetermined size.
6. A method according to claim 1 , wherein identifying the plurality of temporal derivatives comprises identifying a region of proximate temporal derivatives in a spectrum of the plurality of identified high-energy components.
7. A method according to claim 1 , wherein morphologically filtering the identified plurality of temporal derivatives comprises applying a two-dimensional image filter to the plurality of identified temporal derivatives.
8. A method according to claim 1 , wherein estimating the plurality of interference energies comprises initially estimating the interference energies based on a power spectral density of the signal for at least a predetermined period of time and thereafter imposing a temporal monotonic decay on the estimated interference energies.
9. A method according to claim 1 , wherein morphologically filtering the identified plurality of temporal derivatives comprises calculating values for a plurality of interference bins, based at least in part on the plurality of estimated interference energies.
10. A method according to claim 9 , wherein detecting the onsets of the impulsive interferences comprises detecting the onsets of the impulsive interferences based at least in part on the calculated values for the plurality of interference bins of a previous time frame.
11. A method according to claim 1 , further comprising automatically:
determining a starting frequency; and
modifying the plurality of estimated interference energies, so as to enforce a progressively smaller estimated interference energy for progressively higher frequencies, beginning at the determined starting frequency.
12. A method according to claim 11 , further comprising automatically:
calculating at least one of a signal-to-interference ratio (SIR) and a total interference-to-noise ratio (INR); and
based on the calculated at least one of the SIR and the INR, adjusting an operational parameter that influences how the plurality of estimated interference energies are modified.
13. A method according to claim 11 , wherein suppressing the portions of the noisy speech signal comprises subtracting the plurality of modified estimated interference energies from the noisy speech signal to generate the enhanced signal.
14. A method according to claim 1 , wherein suppressing the portions of the noisy speech signal comprises:
modifying the plurality of estimated interference energies based on external information about a presence the noisy speech signal, wind and/or other signal or interference information; and
subtracting the plurality of modified estimated interference energies from the noisy speech signal to generate the enhanced signal.
15. A method according to claim 1 , wherein suppressing the portions of the noisy speech signal comprises:
modifying the plurality of estimated interference energies to enforce a roll-off of the plurality of estimated interference energies with increased frequency above a threshold; and
subtracting the plurality of modified estimated interference energies from the noisy speech signal to generate the enhanced signal.
16. A method according to claim 1 , wherein the impulsive interferences are wind noise.
17. A system, comprising:
a processor and a memory configured to:
receive a noisy speech signal from a microphone of a device;
identify, using the processor, a plurality of high-energy components of the noisy speech signal, wherein energy of each of the plurality of identified high-energy components exceeds a predetermined threshold;
identify a plurality of temporal derivatives of the plurality of identified high-energy components, wherein a temporal derivative comprises changes over time in energies of a frequency component, wherein each of the plurality of identified temporal derivatives is associated with a frequency range, and the frequency ranges associated with the plurality of identified temporal derivatives collectively form a contiguous range of frequencies beginning below a predetermined frequency;
detect onsets of impulsive interferences in the noisy speech signal and estimate a plurality of interference energies in the noisy speech signal, based at least in part on the plurality of identified temporal derivatives, wherein the impulsive interferences correspond to bursts of energy in the noisy speech signal having a substantially random time of occurrence; and
suppress portions of the noisy speech signal having the impulsive interferences, based on the plurality of estimated interference energies to generate an enhanced speech signal for automatic speech recognition.
18. A system according to claim 17 , wherein the temporal differentiator is configured to identify the plurality of temporal derivatives, such that each of the plurality of identified temporal derivatives exceeds a predetermined value.
19. A non-transitory computer-readable medium having instructions stored thereon for reducing impulsive interferences in a noisy speech signal, such that when the instructions are executed by a processor, the processor performs steps including:
receiving the noisy speech signal from a microphone of a device;
identifying a plurality of high-energy components of the noisy speech signal, wherein energy of each of the plurality of identified high-energy components exceeds a predetermined threshold;
identifying a plurality of temporal derivatives of the plurality of identified high-energy components, wherein a temporal derivative comprises changes over time in energies of a frequency component, wherein each of the plurality of identified temporal derivatives is associated with a frequency range, and the frequency ranges associated with the plurality of identified temporal derivatives collectively form a contiguous range of frequencies beginning below a predetermined frequency;
morphologically filtering the identified plurality of temporal derivatives, including detecting onsets of the impulsive interferences and estimating a plurality of interference energies in the noisy speech signal, based at least in part on the plurality of identified temporal derivatives, wherein the impulsive interferences correspond to bursts of energy in the noisy speech signal having a substantially random time of occurrence; and
suppressing portions of the noisy speech signal having the impulsive interferences, based on the plurality of estimated interference energies to generate an enhanced speech signal for automatic speech recognition.