Abstract: A system can include a foundation structure and a sensor. The foundation structure can have a plurality of deck panels configured to support a mattress. The plurality of deck panels can include a head panel. The plurality of deck panels can have a head, a foot, a first side, and a second side, a first edge along the head, a second edge along the foot opposite of the first edge, a third edge along the first side, and a fourth edge along the second side opposite the third edge. The sensor can be configured to detect a sound indicative of a snore. The sensor can be positioned along the third edge or fourth edge of the head panel.

Abstract: A system includes a respiratory device, a mask, a microphone, a speaker, and a control system. The respiratory device is configured to supply pressurized air. The mask is coupled to the respiratory device and configured to engage a user during a sleep session to aid in directing the supplied pressurized air to the user. The microphone is configured to generate audio data. The speaker is configured to emit sound. The control system is configured to analyze the audio data to determine if noise associated with air leaking from the mask is occurring. Responsive to (i) the analysis resulting in a determination that noise associated with air leaking from the mask is occurring, (ii) the respiratory device determining that air is leaking from the mask, or (iii) both, the speaker is caused to emit the sound to aid in masking the noise associated with the air leaking from the mask.

Abstract: In accordance with an embodiment of the present invention, a noise reduction method for speech processing includes cancelling or reducing noise/interference component signal in speech signal enhancement processing, the method comprising estimating the noise/interference component signal by subtracting voice component signal from a first microphone input signal wherein the voice component signal is evaluated as a first replica signal produced by passing a second microphone input signal through a first adaptive filter. Energy variation of the noise/interference component signal is adjusted based on noise stability detection and/or energy explosion detection, wherein the energy of the noise/interference component signal is reduced or smoothed in voice area or energy explosion area if the stable noise is detected and/or the energy explosion is detected.

Abstract: A method for adjusting the performance of an electroacoustic transducer includes receiving, by gain adjustment circuit, a displacement signal corresponding to a relative motion between a magnetic structure of the electroacoustic transducer and a voice coil of the electroacoustic transducer. The method includes detecting, by the gain adjustment circuit, a displacement signal value of the displacement signal as one of meeting or exceeding a displacement signal threshold. The method includes modifying, by the gain adjustment circuit, a loop gain of an active noise reduction loop associated with the electroacoustic transducer when the displacement signal value of the displacement signal one of meets or exceeds the displacement signal threshold.

Abstract: A personal audio device, such as a wireless telephone, includes noise canceling circuit that adaptively generates an anti-noise signal from a reference microphone signal and injects the anti-noise signal into the speaker or other transducer output to cause cancellation of ambient audio sounds. An error microphone may also be provided proximate the speaker to measure the output of the transducer in order to control the adaptation of the anti-noise signal and to estimate an electro-acoustical path from the noise canceling circuit through the transducer. A processing circuit that performs the adaptive noise canceling (ANC) function also either adjusts the frequency response of the anti-noise signal with respect to the reference microphone signal, and/or by adjusting the response of the adaptive filter independent of the adaptation provided by the reference microphone signal.

Abstract: Accepting the speech having the noise superimposed thereon and converting it into a signal on a time axis of the speech, an amplitude component of a speech for each predetermined frequency band of the converted signal on the frequency axis is calculated. Calculating a noise reduction coefficient, the noise component is reduced by multiplying the signal on the frequency axis of the original signal by the calculated noise reduction coefficient. By estimating the target value of the remaining noise for each frequency band, a signal on a frequency axis in which a signal corresponding to a frequency band of which target value estimated by the noise target value is larger than the value of the amplitude component of the signal on the frequency axis of which noise component is reduced is corrected to a signal corresponding to the target value is restored, into a signal on a time axis.

Abstract: During speech processing a filter (11) adjusts a spectral envelope of an input speech signal with a frequency dependent adjustment factor. The adjustment factors for respective spectral components are selected dependent on the input speech signal. The factor is set to a first or second non-zero value, the second value being smaller than the first value, when a strength average for the spectral component is above and below a threshold value respectively.

Abstract: Systems, methods, and apparatus for processing an M-channel input signal are described that include outputting a signal produced by a selected one among a plurality of spatial separation filters. Applications to separating an acoustic signal from a noisy environment are described, and configurations that may be implemented on a multi-microphone handheld device are also described.

Abstract: A method and corresponding apparatus for coded-domain acoustic echo control is presented. An echo control problem is considered as that of perceptually matching an echo signal to a reference signal. A perceptual similarity function that is based on the coded spectral parameters produced by the speech codec is defined. Since codecs introduce a significant degree of non-linearity into the echo signal, the similarity function is designed to be robust against such effects. The similarity function is incorporated into a coded-domain echo control system that also includes spectrally-matched noise injection for replacing echo frames with comfort noise. Using actual echoes recorded over a commercial mobile network, it is shown herein that the similarity function is robust against both codec non-linearities and additive noise. Experimental results further show that the echo-control is effective at suppressing echoes compared to a Normalized Least Mean Squared (NLMS)-based echo cancellation system.