Abstract: Use of spoken input for user devices, e.g. smartphones, can be challenging due to presence of other sound sources. Blind source separation (BSS) techniques aim to separate a sound generated by a particular source of interest from a mixture of different sounds. Various BSS techniques disclosed herein are based on recognition that providing additional information that is considered within iterations of a nonnegative tensor factorization (NTF) model improves accuracy and efficiency of source separation. Examples of such information include direction estimates or neural network models trained to recognize a particular sound of interest. Furthermore, identifying and processing incremental changes to an NTF model, rather than re-processing the entire model each time data changes, provides an efficient and fast manner for performing source separation on large sets of quickly changing data. Carrying out at least parts of BSS techniques in a cloud allows flexible utilization of local and remote sources.

Abstract: Heart rate monitors are plagued by noisy photoplethysmography (PPG) data, which makes it difficult for the monitors to output a consistently accurate heart rate reading. Noise is often caused by motion. Using known methods for processing accelerometer readings that measure movement to filter out some of this noise may help, but not always. The present disclosure describes an improved filtering approach, referred to herein as an iterative frequency-domain mask estimation technique, based on using frequency-domain representation (e.g. STFT) of PPG data and accelerometer data for each accelerometer channel to generate filters for filtering the PPG signal from motion-related artifacts prior to tracking frequency of the heartbeat (heart rate). Implementing this technique leads to more accurate heart rate measurements.

Abstract: Systems and methods for filtering noise from an input signal in a computationally efficient manner are provided. A method includes generating a raw noisy matrix representing the input signal, wherein each element of the raw noisy matrix represents a portion of the input signal, initializing a denoised matrix as equal to the raw noisy matrix, and updating the denoised matrix. Updating the denoised matrix includes iteratively convolving a current version of the denoised matrix with a kernel to generate a convolution matrix, and modifying the denoised matrix based in part on values in the convolution matrix.

Abstract: The present disclosure relates generally to improving acoustic source tracking and selection and, more particularly, to techniques for acoustic source tracking and selection using motion or position information. Embodiments of the present disclosure include systems designed to select and track acoustic sources. In one embodiment, the system may be realized as an integrated circuit including a microphone array, motion sensing circuitry, position sensing circuitry, analog-to-digital converter (ADC) circuitry configured to convert analog audio signals from the microphone array into digital audio signals for further processing, and a digital signal processor (DSP) or other circuitry for processing the digital audio signals based on motion data and other sensor data. Sensor data may be correlated to the analog or digital audio signals to improve source separation or other audio processing.

Abstract: The disclosed apparatus, systems, and methods provide a calibration technique for calibrating a set of microphones. The disclosed calibration technique is configured to calibrate the microphones with respect to a reference microphone and can be used in actual operation rather than a testing environment. The disclosed calibration technique can estimate both the magnitude calibration factor for compensating magnitude sensitivity variations and the relative phase error for compensating phase delay variations. In addition, the disclosed calibration technique can be used even when multiple acoustic sources are present. The disclosed technique is particularly well suited to calibrating a set of microphones that are omnidirectional and sufficiently close to one another.

Abstract: The disclosed apparatus, systems, and methods provide a calibration technique for calibrating a set of microphones. The disclosed calibration technique is configured to calibrate the microphones with respect to a reference microphone and can be used in actual operation rather than a testing environment. The disclosed calibration technique can estimate both the magnitude calibration factor for compensating magnitude sensitivity variations and the relative phase error for compensating phase delay variations. In addition, the disclosed calibration technique can be used even when multiple acoustic sources are present. The disclosed technique is particularly well suited to calibrating a set of microphones that are omnidirectional and sufficiently close to one another.

Abstract: The disclosed apparatus, systems, and methods provide a calibration technique for calibrating a set of microphones. The disclosed calibration technique is configured to calibrate the microphones with respect to a reference microphone and can be used in actual operation rather than a testing environment. The disclosed calibration technique can estimate both the magnitude calibration factor for compensating magnitude sensitivity variations and the relative phase error for compensating phase delay variations. In addition, the disclosed calibration technique can be used even when multiple acoustic sources are present. The disclosed technique is particularly well suited to calibrating a set of microphones that are omnidirectional and sufficiently close to one another.

Abstract: The disclosed apparatus, systems, and methods provide a calibration technique for calibrating a set of microphones. The disclosed calibration technique is configured to calibrate the microphones with respect to a reference microphone and can be used in actual operation rather than a testing environment. The disclosed calibration technique can estimate both the magnitude calibration factor for compensating magnitude sensitivity variations and the relative phase error for compensating phase delay variations. In addition, the disclosed calibration technique can be used even when multiple acoustic sources are present. The disclosed technique is particularly well suited to calibrating a set of microphones that are omnidirectional and sufficiently close to one another.