Abstract: A method of training a device specific cloud-based audio processor includes receiving sensor data captured from multiple sensors at a local device. The method also includes receiving spatial information labels computed on the local device using local configuration information. The spatial information labels are associated with the captured sensor data. Lower layers of a first neural network are trained based on the spatial information labels and sensor data. The trained lower layers are incorporated into a second, larger neural network for audio classification. The second, larger neural network may be retrained using the trained lower layers of the first neural network.

Abstract: A drone system and method. Audio signals are received via one or more microphones positioned relative to a location on a drone and one or more of the audio signals are identified as of interest. Flight characteristics of the drone are then controlled based on the audio signals that are of interest.

Abstract: A device includes a memory and a processor. The memory is configured to store a threshold. The processor is configured to authenticate a user based on authentication data. The processor is also configured to, in response to determining that the user is authenticated, generate a correlation score indicating a correlation between a first signal received from a first sensor and a second signal received from a second sensor. The processor is also configured to determine liveness of the user based on a comparison of the correlation score and the threshold.

Abstract: Disclosed is a feature extraction and classification methodology wherein audio data is gathered in a target environment under varying conditions. From this collected data, corresponding features are extracted, labeled with appropriate filters (e.g., audio event descriptions), and used for training deep neural networks (DNNs) to extract underlying target audio events from unlabeled training data. Once trained, these DNNs are used to predict underlying events in noisy audio to extract therefrom features that enable the separation of the underlying audio events from the noisy components thereof.

Abstract: A method for speech restoration by an electronic device is described. The method includes obtaining a noisy speech signal. The method also includes suppressing noise in the noisy speech signal to produce a noise-suppressed speech signal. The noise-suppressed speech signal has a bandwidth that includes at least three subbands. The method further includes iteratively restoring each of the at least three subbands. Each of the at least three subbands is restored based on all previously restored subbands of the at least three subbands.

Abstract: Disclosed is a feature extraction and classification methodology wherein audio data is gathered in a target environment under varying conditions. From this collected data, corresponding features are extracted, labeled with appropriate filters (e.g., audio event descriptions), and used for training deep neural networks (DNNs) to extract underlying target audio events from unlabeled training data. Once trained, these DNNs are used to predict underlying events in noisy audio to extract therefrom features that enable the separation of the underlying audio events from the noisy components thereof.

Abstract: A method for speech restoration by an electronic device is described. The method includes obtaining a noisy speech signal. The method also includes suppressing noise in the noisy speech signal to produce a noise-suppressed speech signal. The noise-suppressed speech signal has a bandwidth that includes at least three subbands. The method further includes iteratively restoring each of the at least three subbands. Each of the at least three subbands is restored based on all previously restored subbands of the at least three subbands.

Abstract: A method for extracting coalbed gas. A wellhead device delivers power fluid into a downhole power fluid pipe in a well shaft, and conveys the fluid to a pump in a pump cylinder connected with the downhole power fluid pipe. The pump sucks in formation fluid via a suction inlet, mixes the fluid with the power fluid to produce a mixed fluid, and conveys the mixed fluid to ground surface. The mixed fluid containing coal dust travels at a flow rate greater than a sedimentation rate of the coal dust, passes though the wellhead device, and flows to the ground surface, thereby preventing a sedimentation of the coal dust. The suction inlet of the pump reaches a lower boundary of a coalbed so as to prevent coal dust from burying the coalbed, and the coalbed gas automatically shoots through an annular space of a well shaft casing.

Abstract: A method for speech modeling by an electronic device is described. The method includes obtaining a real-time noise reference based on a noisy speech signal. The method also includes obtaining a real-time noise dictionary based on the real-time noise reference. The method further includes obtaining a first speech dictionary and a second speech dictionary. The method additionally includes reducing residual noise based on the real-time noise dictionary and the first speech dictionary to produce a residual noise-suppressed speech signal at a first modeling stage. The method also includes generating a reconstructed speech signal based on the residual noise-suppressed speech signal and the second speech dictionary at a second modeling stage.

Abstract: A method for enhancing an audio signal by an electronic device is described. The method includes determining formant peaks based on an audio signal. The method also includes generating formant peak models. Generating formant peak models includes individually modeling each formant peak. The method further includes generating a global envelope based on the formant peak models.

Abstract: Operating software commitment may be provided. First, a subscriber device may be configured using a factory software and a service provider software may be downloaded. Next, it may be verified that the subscriber device is properly configured. In response to verifying that the subscriber device is properly configured, the service provider software may then be committed to the subscriber device.