Abstract:
A method of dominant speech extraction is provided that includes acquiring a primary audio signal from a microphone and at least one additional audio signal from at least one additional microphone, wherein the acquired audio signals include speech and noise, decomposing each acquired audio signal into a low frequency sub-band signal and a high frequency sub-band signal, applying speech suppression beamforming to the low frequency sub-band signals to generate a reference channel having an estimate of noise in the low frequency sub-band signals, applying noise cancellation to the low frequency sub-band signal of the primary audio signal using the reference channel to generate a first signal having a low frequency estimate of the speech, applying noise suppression beamforming to the high frequency sub-band signals to generate a second signal having a high frequency estimate of the speech, and combining the first and second signals to generate a full-band audio signal.
Abstract:
A method and apparatus for active noise canceling. The method includes retrieving an input sample from at least one of a feedback or feedforward microphone digitized through the sigma-delta converter, retrieving the input sample and a related filter, wherein the filter is customized to the particular headset, outputting a filtered signal through a speaker without any interpolation and reducing order of CIC filters, and outputting a response sharply tapered down.
Abstract:
An active noise cancellation (“ANC”) unit receives audio signals from a user-operated device through a connection. In response to the audio signals, the ANC unit causes at least one speaker to generate sound waves. The ANC unit receives a set of parameters from the user-operated device through the connection. The connection is at least one of: an audio cable; and a wireless connection. The set of parameters represents a user-specified combination of ANC properties. The ANC unit automatically adapts itself to implement the set of parameters for substantially achieving the user-specified combination of ANC properties in operations of the ANC unit.
Abstract:
A method includes: transmitting, via a signal generator, an electrical driving signal, the electrical driving signal having a mean square error; transmitting, via a wave generating component, a Lamb wave, the Lamb wave having many different modes; estimating, via an estimating component, a propagation parameter associated with the Lamb wave; and estimating, via an estimating component, a thickness of a material.
Abstract:
A method of dominant speech extraction is provided that includes acquiring a primary audio signal from a microphone and at least one additional audio signal from at least one additional microphone, wherein the acquired audio signals include speech and noise, decomposing each acquired audio signal into a low frequency sub-band signal and a high frequency sub-band signal, applying speech suppression beamforming to the low frequency sub-band signals to generate a reference channel having an estimate of noise in the low frequency sub-band signals, applying noise cancellation to the low frequency sub-band signal of the primary audio signal using the reference channel to generate a first signal having a low frequency estimate of the speech, applying noise suppression beamforming to the high frequency sub-band signals to generate a second signal having a high frequency estimate of the speech, and combining the first and second signals to generate a full-band audio signal.
Abstract:
A method includes: transmitting, via a signal generator, an electrical driving signal, the electrical driving signal having a mean square error; transmitting, via a wave generating component, a Lamb wave, the Lamb wave having many different modes; estimating, via an estimating component, a propagation parameter associated with the Lamb wave; and estimating, via an estimating component, a thickness of a material.
Abstract:
Microphone signals are received from a microphone. The microphone signals represent first sound waves. A determination is made about a type of noise that likely exists in the first sound waves. In response to the type of noise, cancellation signals are generated by filtering the microphone signals with at least one of: a first filter in response to the type of noise indicating that a first type of noise likely exists in the first sound waves; and a second filter in response to the type of noise indicating that a second type of noise likely exists in the first sound waves. In response to the cancellation signals, second sound waves are output from a speaker for cancelling at least some noise in the first sound waves.
Abstract:
A method and apparatus for active noise canceling. The method includes retrieving an input sample from at least one of a feedback or feedforward microphone digitized through the sigma-delta converter, retrieving the input sample and a related filter, wherein the filter is customized to the particular headset, outputting a filtered signal through a speaker without any interpolation and reducing order of CIC filters, and outputting a response sharply tapered down.
Abstract:
Microphone signals are received from a microphone. The microphone signals represent first sound waves. A determination is made about a type of noise that likely exists in the first sound waves. In response to the type of noise, cancellation signals are generated by filtering the microphone signals with at least one of: a first filter in response to the type of noise indicating that a first type of noise likely exists in the first sound waves; and a second filter in response to the type of noise indicating that a second type of noise likely exists in the first sound waves. In response to the cancellation signals, second sound waves are output from a speaker for cancelling at least some noise in the first sound waves.