Abstract: Features are disclosed for measuring and correcting clock drift and propagation delay in an audio system through one or more waveforms embedded in an audio signal. A first device in communication with a speaker may be configured to obtain an audio signal and insert one or more waveforms into the audio signal. For example, the waveforms may be inserted during an interval of time. A second device in communication with a microphone may be configured to detect sound as an audio input signal. The second device may obtain a spectral representation of the audio input signal and determine a rotation based on the spectral representation at the frequency of at least one of the inserted waveforms. Clock drift may be determined based on the rotation.

Abstract: An echo cancellation system that performs audio beamforming to separate audio input into multiple directions and determines a target signal and a reference signal from the multiple directions. For example, the system may detect a strong signal associated with a speaker and select the strong signal as a reference signal, selecting another direction as a target signal. The system may determine a speech position and may select the speech position as a target signal and an opposite direction as a reference signal. The system may create pairwise combinations of opposite directions, with an individual direction being selected as a target signal and a reference signal. The system may select a fixed beamformer output for the target signal and an adaptive beamformer output for the reference signal, or vice versa. The system may remove the reference signal (e.g., audio output by the loudspeaker) to isolate speech included in the target signal.

Abstract: An echo cancellation system that performs audio beamforming to separate audio input into multiple directions and determines a target signal and a reference signal from the multiple directions. For example, the system may detect a strong signal associated with a speaker and select the strong signal as a reference signal, selecting another direction as a target signal. The system may determine a speech position and may select the speech position as a target signal and an opposite direction as a reference signal. The system may create pairwise combinations of opposite directions, with an individual direction being selected as a target signal and a reference signal. The system may select a fixed beamformer output for the target signal and an adaptive beamformer output for the reference signal, or vice versa. The system may remove the reference signal (e.g., audio output by the loudspeaker) to isolate speech included in the target signal.

Abstract: An echo cancellation system performs audio beamforming to separate audio input into multiple directions (e.g., target signals) and generates multiple audio outputs using two acoustic echo cancellation (AEC) circuits. A first AEC removes a playback reference signal (generated from a signal sent a loudspeaker) to isolate speech included in the target signals. A second AEC removes an adaptive reference signal (generated from microphone inputs corresponding to audio received from the loudspeaker) to isolate speech included in the target signals. A beam selector receives the multiple audio outputs and selects the first AEC or the second AEC based on a linearity of the system. When linear (e.g., no distortion or variable delay between microphone input and playback signal), the beam selector selects an output from the first AEC based on signal to noise (SNR) ratios. When nonlinear, the beam selector selects an output from the second AEC.

Abstract: An echo cancellation system that uses a combined reference signal using a playback reference signal and an adaptive reference signal. The playback reference signal is generated from a playback signal sent to a loudspeaker and the adaptive reference signal is generated using beamforming on microphone inputs corresponding to audio received from the loudspeaker. The system applies a low pass filter to the playback reference signal and applies a high pass filter to the adaptive reference signal to generate the combined reference signal. The system may remove the combined reference signal from target signals associated with the microphone inputs to isolate speech included in the target signals.

Abstract: An echo cancellation system that detects and compensates for differences in sample rates between the echo cancellation system and a set of wireless speakers based on a frequency-domain analysis. The system generates Fourier transforms for a microphone signal and a reference signal and determines a series of angles for individual frames. For each tone in the Fourier transforms, the system determines the angles and uses linear regression to determine an individual frequency offset associated with the tone. Using the individual frequency offsets associated with the tones, the system uses linear regression to determine an overall frequency offset between the audio sent to the speakers and the audio received from a microphone. Based on the overall frequency offset, samples of the audio are added or dropped when echo cancellation is performed, compensating for the frequency offset.

Abstract: A multi-channel echo cancellation system that dynamically adapts to changes in acoustic conditions. The system does not require a sequence of “start-up” tones to determine the impulse responses. Rather, the adaptive filters approximate estimated transfer functions for each channel. A secondary adaptive filter adjusts cancellation to adapt to changes in the actual transfer functions over time after the adaptive filters have been trained, even if the reference signals are not unique relative to each other.

Abstract: An echo cancellation system that detects and compensations for differences in sample rates between the echo cancellation system and a set of wireless speakers based on a frequency-domain analysis of estimated impulse response coefficients. The system tracks the real and imaginary number components of the coefficients, and determines a “rotation” of the coefficients over time caused by a frequency offset between the audio sent to the speakers and the audio received from a microphone. Based on the rotation, samples of the audio are added or dropped when echo cancellation is performed, compensating for the frequency offset.

Abstract: An acoustic echo cancellation (AEC) system that detects and compensates for differences in sample rates between the AEC system and a set of wireless speakers based on a search-based trial-and-error technique. The system individually determines a frequency offset for each microphone-speaker pair using an iterative process, determining an echo-return loss enhancement (ERLE) value for each offset that is tried, and selecting the frequency offset associated with the largest ERLE value.

Abstract: Features are disclosed for performing efficient dereverberation of speech signals captured with single- and multi-channel sensors in networked audio systems. Such features could be used in applications requiring automatic recognition of speech captured with sensors. Dereverberation is performed in the sub-band domain, and hence provides improved dereverberation performance in terms of signal quality, algorithmic delay, computational efficiency, and speed of convergence.

Abstract: A system may be configured to interact with a user through speech using a first and second audio devices, where the first device produces audio and the second device captures audio. The second device may be configured to perform acoustic echo cancellation with respect to a microphone signal based on a reference signal provided by the first device. The reference and microphone signals may have the same nominal signal rates. However, the signal rates may drift from each other over time. In order to synchronize the rates of the signals, each of the devices maintains a signal index. The second device compares the values of the two signal indexes over time to determine rate differences between the reference and microphone signals and then corrects for the rate differences.

Abstract: Features are disclosed for performing acoustic echo cancellation using random noise. The output may be used to perform speech recognition. Random noise may be introduced into a reference signal path and into a microphone signal path. The random noise introduced into the microphone signal path may be transformed based on an estimated echo path and then combined with microphone output. The random noise introduced into the reference signal path may be combined with a reference signal and then transformed. In some embodiments, the random noise in the reference signal path may be used in the absence of another reference signal, allowing the acoustic echo canceler to be continuously trained.

Abstract: Features are disclosed for adaptively estimating propagation delay in an audio system. A first device in communication with a speaker may be configured produce sound based on an audio playback signal. A second device in communication with one or more microphones may be configured to detect sound as a microphone signal. The second device may perform acoustic echo cancellation using a first propagation delay parameter and determine a first echo return loss enhancement. The second device may perform acoustic echo cancellation using a second propagation delay parameter and determine a second echo return loss enhancement. A propagation delay between the audio playback signal and the microphone signal may be adaptively estimated based on a comparison of the first and second echo return loss enhancements.

Abstract: Features are disclosed for measuring and correcting clock drift and propagation delay in an audio system through one or more waveforms embedded in an audio signal. A first device in communication with a speaker may be configured to obtain an audio signal and insert one or more waveforms into the audio signal. For example, the waveforms may be inserted during an interval of time. A second device in communication with a microphone may be configured to detect sound as an audio input signal. The second device may obtain a spectral representation of the audio input signal and determine a rotation based on the spectral representation at the frequency of at least one of the inserted waveforms. Clock drift may be determined based on the rotation.

Abstract: Features are disclosed for estimating a noise level using a variable step size. An acoustic echo canceller (AEC) may be configured to perform echo cancellation. The acoustic echo canceller may determine an estimated echo using a playback signal. The acoustic echo canceller also may determine an estimated error using the estimated echo and a microphone signal. A variable step size may be determined using the estimated error and the microphone signal. Noise reduction may be performed using the variable step size.

Abstract: A acoustic echo canceller (AEC) system may be configured to perform echo cancellation in the frequency domain. Features are disclosed for determining an estimated echo in the frequency domain using adaptive filters. An adaptive filter corresponding to a frequency bin can comprise a plurality of filter taps. Additional features are disclosed for updating the adaptive filter. In addition, a frequency-bin dependent step size controller may be used to control a step size used in updating the adaptive filters. Features are disclosed for determining the frequency-bin dependent step size.

Abstract: A multi-tone transceiver including: a transform component, a tone selector, an error detector, an aggregator and an oscillator. The transform component transforms received communications from the time domain to the frequency domain. The tone selector selects a sub-set of the received tones which exhibit an elevated signal-to-noise ratio (SNR) as a clock recovery tone set (CRTS) and drops and add tones to the CRTS as required by changes in the SNR of the individual tones. The error detector detects phase errors in each received tone of the CRTS. The aggregator calculates an average aggregate phase error from all tones in the CRTS. The oscillator controls clocking of the transceiver. The oscillator is responsive to the average aggregate phase error to adjust a clock phase in a direction which reduces a phase error with a clock on the opposing transceiver.

Abstract: An equalization method and apparatus for a communication system having a first transceiver device that communicates with each of a plurality of second transceiver devices receives a data transmission over a subset of frequency sub-carriers allotted to each second transceiver device. The communication channel between first transceiver device and the plurality of second transceiver devices is partitioned in a plurality of frequency sub-carriers of which the frequency sub-carriers allotted to a second transceiver device is a subset. The data transmission is transformed from a time-domain transmission to a frequency domain transmission. An equalization filter is applied separately to each of the frequency sub-carriers within the subset of frequency sub-carriers.

Abstract: A multi-tone transceiver including: a transform component, a tone selector, an error detector, an aggregator and an oscillator. The transform component transforms received communications from the time domain to the frequency domain. The tone selector selects a sub-set of the received tones which exhibit an elevated signal-to-noise ratio (SNR) as a clock recovery tone set (CRTS) and drops and add tones to the CRTS as required by changes in the SNR of the individual tones. The error detector detects phase errors in each received tone of the CRTS. The aggregator calculates an average aggregate phase error from all tones in the CRTS. The oscillator controls clocking of the transceiver. The oscillator is responsive to the average aggregate phase error to adjust a clock phase in a direction which reduces a phase error with a clock on the opposing transceiver.

Abstract: A buffered crossbar switch is provided with a buffer to port relationship that supports cells and packets of variable size. A novel scheduler is provided that allows for an efficient crossbar switch, where the relationship between the number of internal buffers is less than the number of ports squared. This allows for a switch that can be implemented that requires less buffer memory.