Abstract: Techniques for using multiple machine learning (ML) models, with varying compute costs, for ASR processing is described. The system may include an arbitrator component configured to determine which ML model is to be used to process an audio frame from a sequence of audio frames representing a spoken natural language input. The arbitrator component may switch between the ML models, on a frame-by-frame basis, to reduce an overall compute cost for the entire spoken natural language input. The outputs of the different ML models may be combined to determine the final output for the entire spoken natural language input.

Abstract: Some devices may perform processing using machine learning models trained at a centralized system and distributed to the device. The centralized system may update the machine learning model and distribute the update to the device (or devices). To reduce the size of an update, the centralized system may train a model update object, which may be smaller in size than the model itself and thus more suitable for sending to the device(s). A device may receive the model update object and use it to update the on-device machine learning model; for example, by changing some parameters of the model. Parameters left unchanged during the update may retain their previous value. Thus, using the model update object to update the on-device model may result in a more accurate updated model when compared to sending an updated model compressed to a size similar to that of the model update object.

Abstract: A histotripsy therapy system configured for the treatment of tissue is provided, which may include any number of features. Provided herein are systems and methods that provide efficacious non-invasive and minimally invasive therapeutic, diagnostic and research procedures. In particular, provided herein are optimized systems and methods that provide targeted, efficacious histotripsy in a variety of different regions and under a variety of different conditions without causing undesired tissue damage to intervening/non-target tissues or structures.

Abstract: A method for imaging a room by a controller includes requesting a signal, indicative of a measurement of a parameter, from a sensor associated with a position and direction of a mobile platform in the room, wherein the measurement from the sensor includes background noise, distortions, and a foreground signal of interest, in response to the mobile platform reaching a new position, requesting a second measurement of the parameter from the sensor associated with the new position of the mobile platform, spatially aggregating the signal from the sensor and associated position and direction to create an energy map via spatio-dynamic beamforming, wherein the background noise and distortions are reduced, by spatially averaging beamformed information acquired across multiple locations to synthesize signals indicative of the foreground signal of interest, analyzing the energy map to identify a state of an apparatus in the room, and outputting a foreground beamformed image.

Abstract: A mobile platform for calibrated data acquisition includes a transceiver within the mobile platform, a locomotion unit configured to move the mobile platform within an area, a sensor coupled with the locomotion unit and configured to output a signal, and a controller that is configured to request a measurement of a parameter from the sensor, remove from the measurement, background noise associated with the mobile platform, thereby focusing the measurement to foreground noise, in response to the mobile platform reaching a new position and direction, request a second measurement of the parameter from the sensor, remove from the second measurement, background noise associated with the mobile platform at the new position, aggregate the signal from the sensor and associated position and direction to create an energy map via spatio-dynamic beamforming, and analyzing the energy map to identify a state of an apparatus in the area.

Abstract: A method for imaging a room by a controller includes requesting a signal, indicative of a measurement of a parameter, from a sensor associated with a position and direction of a mobile platform in the room, wherein the measurement from the sensor includes background noise, distortions, and a foreground signal of interest, in response to the mobile platform reaching a new position, requesting a second measurement of the parameter from the sensor associated with the new position of the mobile platform, spatially aggregating the signal from the sensor and associated position and direction to create an energy map via spatio-dynamic beamforming, wherein the background noise and distortions are reduced, by spatially averaging beamformed information acquired across multiple locations to synthesize signals indicative of the foreground signal of interest, analyzing the energy map to identify a state of an apparatus in the room, and outputting a foreground beamformed image.

Abstract: A method for self-diagnosing a data acquisition system for acquiring calibrated images of an area by a controller includes requesting a signal, from a sensor associated with a mobile platform in the area, removing from the signal, background noise associated with the mobile platform, thereby focusing the measurement to a foreground signal, wherein the background noise is removed from the foreground signal via a subspace approximation using singular value, requesting a previous-in-time signal indicative of a previous-in-time measurement of the parameter, wherein previous-in-time background noise is removed from a previous-in-time foreground signal via subspace approximation using singular value decomposition and in response to a change detection indicating a difference between a spectrogram of the background noise and a previous-in-time spectrogram of the previous-in-time background noise exceeding a predetermined threshold at a predetermined frequency, outputting a status signal indicative of a change in oper

Abstract: A mobile platform for calibrated data acquisition includes a transceiver within the mobile platform, a locomotion unit configured to move the mobile platform within an area, a sensor coupled with the locomotion unit and configured to output a signal, and a controller that is configured to request a measurement of a parameter from the sensor, remove from the measurement, background noise associated with the mobile platform, thereby focusing the measurement to foreground noise, in response to the mobile platform reaching a new position and direction, request a second measurement of the parameter from the sensor, remove from the second measurement, background noise associated with the mobile platform at the new position, aggregate the signal from the sensor and associated position and direction to create an energy map via spatio-dynamic beamforming, and analyzing the energy map to identify a state of an apparatus in the area.

Abstract: A system for measuring a first physical parameter includes a mechanical device configured to operate based on the first physical parameter, and a source sensor coupled with the mechanical device and configured to output a signal indicative of the first physical parameter that is based on a second physical parameter and a forward mapping function, wherein the forward mapping function is learned during a system training phase in which pairwise first physical parameter data from a first physical parameter sensor is forward mapped from second physical parameter data from the source sensor.