Abstract: A system configured to improve noise cancellation by reducing attenuation of local speech in proximity to a device. When the local speech is present in both a target signal and a reference signal, performing noise cancellation to remove the reference signal inadvertently attenuates the local speech. To prevent this, the system may perform first noise cancellation to identify frequency bands associated with the local speech and may generate a modified reference signal based on the frequency bands. For example, the system may generate the modified reference signal by applying attenuation to first frequencies associated with the local speech and/or gain to second frequencies that are not associated with the local speech. The system may generate final output audio data by performing noise cancellation using the modified reference signal.

Abstract: A system configured to improve beamforming by using deep neural networks (DNNs). The system can use one trained DNN to focus on a first person speaking an utterance (e.g., target user) and one or more trained DNNs to focus on noise source(s) (e.g., wireless loudspeaker(s), a second person speaking, other localized sources of noise, or the like). The DNNs may generate time-frequency mask data that indicates individual frequency bands that correspond to the particular source detected by the DNN. Using this mask data, a beamformer can generate beamformed audio data that is specific to a source of noise. The system may perform noise cancellation to isolate first beamformed audio data associated with the target user by removing second beamformed audio data associated with noise source(s).

Abstract: A distributed voice controlled system has a primary assistant and at least one secondary assistant. The primary assistant has a housing to hold one or more microphones, one or more speakers, and various computing components. The secondary assistant is similar in structure, but is void of speakers. The voice controlled assistants perform transactions and other functions primarily based on verbal interactions with a user. The assistants within the system are coordinated and synchronized to perform acoustic echo cancellation, selection of a best audio input from among the assistants, and distributed processing.

Abstract: In one embodiment, a device in a network observes traffic between a client and a server for an encrypted session. The device makes a determination that a server certificate should be obtained from the server. The device, based on the determination, sends a handshake probe to the server. The device extracts server certificate information from a handshake response from the server that the server sent in response to the handshake probe. The device uses the extracted server certificate information to analyze the traffic between the client and the server.

Abstract: An audio capture device that incorporates a beamformer and beam-specific trigger word detection. Audio data from each beam is processed by a low power trigger word detector, such as a neural network or other trained model to detect if audio data (such as an audio frame or feature vector corresponding thereto) likely includes part of a trigger word. The beam that either most strongly represents a trigger word portion or represents a trigger word portion most early in time may be selected for further processing such as speech processing or confirmation by a more robust power intensive trigger word detector.

Abstract: A wearable computer is configured to use beamforming techniques to isolate a user's speech from extraneous audio signals occurring within a physical environment. A microphone array of the wearable computer may generate audio signal data from an utterance from a user's mouth. A motion sensor(s) of the wearable computer may generate motion data from movement of the wearable computer. This motion data may be used to determine a direction vector pointing from the wearable computer to the user's mouth, and a beampattern may be defined that has a beampattern direction in substantial alignment with the determined direction vector to focus the microphone array on the user's mouth for speech isolation.

Abstract: A distributed voice controlled system has a primary assistant and at least one secondary assistant. The primary assistant has a housing to hold one or more microphones, one or more speakers, and various computing components. The secondary assistant is similar in structure, but is void of speakers. The voice controlled assistants perform transactions and other functions primarily based on verbal interactions with a user. The assistants within the system are coordinated and synchronized to perform acoustic echo cancellation, selection of a best audio input from among the assistants, and distributed processing.

Abstract: Systems and methods for disabling adaptive echo cancellation functionality for a temporal window are provided herein. In some embodiments, audio data may be received by a voice activated electronic device, where the audio data may include an utterance of a wakeword that may be subsequently followed by additional speech. A start time of when the wakeword began to be uttered may be determined by the voice activated electronic device, and the voice activated electronic device may also send the audio data to a backend system. Adaptive echo cancellation functionality may be disabled at the start time. The backend system may determine an end time of the speech, and may provide an indication to the voice activated electronic device of the end time, which in turn may cause the voice activated electronic device to enable the adaptive echo cancellation functionality at the end time.

Abstract: An improved fluid delivery system and method that directly controls the concentration of constituent components in a fluid mixture delivered, for example, to a process chamber. Pressure of the fluid mixture can also be directly controlled. A concentration sensor capable of measuring concentration of all of the constituent components in a fluid mixture is used to provide signals used to vary the flow rate of constituent gases under a closed loop feedback system. The signal output of one or more pressure sensors can also be used to provide a signal used to vary the flow rate of constituent gases under a closed loop feedback system. By directly controlling these two extremely important process variables, embodiments of the present invention provide a significant advantage in measurement accuracy over the prior art, enable real-time process control, reduce system level response time, and allow for a system with a significant footprint reduction.

Abstract: An audio device may be configured to produce output audio and to capture input audio for speech recognition. In some cases, a second device may also be used to capture input audio to improve isolation of input audio with respect to the output audio. In addition, acoustic echo cancellation (AEC) may be used to remove components of output audio from input signals of the first and second devices. AEC may be implemented by an adaptive filter based on dynamically optimized filter coefficients. The filter coefficients may be analyzed to detect situations in which the first and second devices are too close to each other, and the user may then be prompted to increase the distance between the two devices.

Abstract: An acoustic echo cancellation (AEC) system that detects and compensates for differences in delay times between the AEC system and a set of wireless speakers. The filter coefficients used for AEC are adjusted based on the determined delay time to correct for frequency domain signal rotation.

Abstract: A speech-based audio device may be configured to detect a user-uttered wake expression. For example, the audio device may generate a parameter indicating whether output audio is currently being produced by an audio speaker, whether the output audio contains speech, whether the output audio contains a predefined expression, loudness of the output audio, loudness of input audio, and/or an echo characteristic. Based on the parameter, the audio device may determine whether an occurrence of the predefined expression in the input audio is a result of an utterance of the predefined expression by a user.

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 acoustic interference cancellation system that performs beamforming using a subset of microphones from a microphone array. For example, a first group of microphones from an array can be used to generate target signals that focus on the direction of the desired speech in the audio and a second group of microphones from the array can be used to generate reference signals that include the environmental noise, audio from a loudspeaker, etc. The reference signals of the second group of microphones can then be used to isolate the actual speech from the target signals of the first group of microphones. The microphone array can be three dimensional, allowing a device to simplify beamforming calculations by selecting subsets of microphones along different planes. In addition, directional microphones and remote microphones may be used to improve a quality of the reference signals.

Abstract: In a speech-based system, a wake word or other trigger expression is used to preface user speech that is intended as a command. The system receives multiple directional audio signals, each of which emphasizes sound from a different direction. The trigger expression is detected in an individual directional audio signal by comparing a confidence score with a confidence threshold. An individual confidence threshold is specified for each directional audio signal. The confidence thresholds are adjusted during operation of the system based on performance information that is generated during operation of the system. As an example, performance information may include the number of times that the trigger expression has been detected in each of the directional audio signals.

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: Embodiments of systems and methods are described for determining which of a plurality of beamformed audio signals to select for signal processing. In some embodiments, a plurality of audio input signals are received from a microphone array comprising a plurality of microphones. A plurality of beamformed audio signals are determined based on the plurality of input audio signals, the beamformed audio signals comprising a direction. A plurality of signal features may be determined for each beamformed audio signal. Smoothed features may be determined for each beamformed audio signal based on at least a portion of the plurality of signal features. The beamformed audio signal corresponding to the maximum smoothed feature may be selected for further processing.

Abstract: An echo cancellation system that generates multiple output paths, enabling Automatic Speech Recognition (ASR) processing in parallel with voice communication. For single direction AEC (e.g., ASR processing), the system prioritizes speech from a single user and ignores other speech by selecting a single directional output from a plurality of directional outputs as a first output path. For multi-directional AEC (e.g., voice communication), the system includes all speech by combining the plurality of directional outputs as a second output path. The system may use a weighted sum technique, such that each directional output is represented in the combined output based on a corresponding signal metric, or an equal weighting technique, such that a first group of directional outputs having a higher signal metric may be equally weighted using a first weight while a second group of directional outputs having a lower signal metric may be equally weighted using a second weight.