Abstract: Embodiments of the present disclosure provide systems and methods directed to directional audio source separation. An example method comprising: receiving a plurality of input signals by a plurality of microphones: generating a plurality of beamformed signals based on the plurality of input signals: providing the plurality of beamformed signals and the plurality of input signals to a neural network, wherein the neural network is trained to generate directional signals based on sample beamformed signals and sample input signals: generating an output directional signal using the neural network based on the plurality of input signals and the plurality of beamformed signals: and providing the directional signal to a speaker.

Abstract: A system that performs wall detection and localization to determine a position of a device relative to acoustically reflective surfaces. The device emits an audible sound including a frequency modulated signal and captures reflections of the audible sound. The frequency modulated signal enables the device to determine an amplitude of the reflections at different time-of-arrivals, which corresponds to a direction of the reflection. The device then performs beamforming to generate a 2D intensity map that represents an intensity of the reflections at each spatial location around the device. The device detects wall(s) in proximity to the device by identifying peak intensities represented in the 2D intensity map. In some examples, instead of performing beamforming, the device can perform directional wall detection by physically rotating the device and emitting the audible sound in multiple directions. The device may perform ultrasonic wall detection using ultrasonic sound frequencies.

Abstract: Techniques for monitoring devices to use ultrasonic signals to detect and track the locations of moving objects in an environment. To determine distance information, the monitoring devices emit a frequency-modulated continuous wave (FMCW) signal at an ultrasound frequency range. Reflections of the FMCW ultrasonic signal are used to generate time-of-arrival (TOA) profiles that indicate distances between the monitoring device and objects in the environment. The reflections can be processed to suppress undesirable interferences, such as reflections off non-mobile objects in the environment (e.g., walls, furniture, etc.), vibrations off the floorings or the ceilings, etc. After processing the reflections, a heatmap can be used to plot the intensity of the reflections for the different TOAs of the reflections, and depict the movement of the user over time. Finally, a Kalman filter is used to smooth the peaks in the intensity values on the plot, and determine the trajectory of the human.

Abstract: Examples of systems and methods are described for detecting heart beats of a subject. The systems and methods may be based on motion of the subject due to cardiac activity, and may operate without contact with the subject. Example systems may provide an interrogation signal to the subject. Reflected signals from the subject are incident on a microphone array. The reflected signals may be processed and beamformed using a set of beamforming weights. The beamforming weights may be selected in a manner to reduce components of the reflected signals due to breathing motion of the subject while increasing the relative contribution of the reflected signals due to cardiac activity. The beamformed signal may provide a waveform indicative of heart beats. Inter-beat intervals, heart rates, and/or other health metrics may be calculated based on the waveform.

Abstract: Embodiments of the present disclosure provide systems and methods directed to contactless motion tracking. In operation, a speaker may provide an acoustic signal to, for example, a subject. A microphone array may receive a reflected acoustic signal, where the received reflected signal is responsive to the acoustic signal reflecting off the subject. A computing device may extraction motion data of the subject based on the received reflected acoustic signal. Various motion data extraction methods are described herein. The motion data may include respiration motion, coarse movement motion, respiration rate, and the like. Using the extracted motion data, the processor may identify at least one health condition and/or sleep anomaly corresponding to the subject. In some examples, beamforming is implemented to aid in contactless motion tracking.

Abstract: Systems and methods for facilitating acoustic-based localization and motion tracking in the presence of multipath, wherein, in operation, acoustic signals are transmitted from a speaker to a microphone array, a processor coupled to the microphone array calculates the 1 D distance between a microphone and/or each microphones of the microphone array and the speaker of a user device by first filtering out multipath signals with large time-of-arrival values relative to the time-of-arrival value of the direct path signal, then extracting out the phase value of the residual multipath signals and direct path signal, using the calculated 1 D distances, the processor may then calculate the intersection of the 1 D distances to determine the 3D location of the speaker to enable sub-millimeter accuracy of 1 D distance between a microphone of a microphone array and a speaker of a user device to enable smaller separation between the microphones of the microphone array.