Abstract:
Methods, apparatus, systems, and articles of manufacture to detect the location of sound sources external to computing devices are disclosed. An apparatus, to determine a direction of a source of a sound relative to a computing device, includes a cross-correlation analyzer to generate a vector of values corresponding to a cross-correlation of first and second audio signals corresponding to the sound. The first audio signal is received from a first microphone of the computing device. The second audio signal is received from a second microphone of the computing device. The apparatus also includes a location analyzer to use a machine learning model and a set of the values of the vector to determine the direction of the source of the sound.
Abstract:
A system is described herein. The system includes at least one hardware processor that is configured to identify a pre-determined acoustic barrier filter, wherein the acoustic barrier filter coincides with the physical acoustic barrier and receive an audio signal within a time window at the first microphone and the second microphone. The hardware processor is also configured to calculate a first measure of variability, a second measure of variability, a third measure of variability, and a fourth measure of variability. The hardware processor further concatenates the first measure of variability, the second measure of variability, the third measure of variability, and the fourth measure of variability to form a feature vector, and inputs the feature vector into a location classifier to obtain an audio source location.
Abstract:
Embodiments of the present disclosure provide techniques and configurations for an apparatus to determine a command to the apparatus, based on vibration patterns. In one instance, the apparatus may include a body with at least one surface to receive one or more user inputs; at least one sensor disposed to be in contact with the body to detect vibration manifested by the surface in response to the user input, and generate a signal indicative of vibration detected; and a controller coupled with the sensor, to process the vibration-indicative signal, to identify a vibration pattern, and determine a command based at least in part on the vibration pattern, based at least in part on a result of the process of the signal. The command may be provided to interact, operate, or control the apparatus. Other embodiments may be described and/or claimed.
Abstract:
A system for sound capture and generation via nasal vibration is described. In embodiments the system includes eyeglasses that include at least a frame that is wearable by a user. Sensing circuitry is mounted to the frame, and a device is incorporated into the frame. The sensing circuitry includes at least one sensor, wherein the sensor can passively sense voice vibration induced in the user's nose, and/or which may actively induce audio vibration in the user's nose based on audio data.
Abstract:
Embodiments of the present disclosure provide techniques and configurations for an apparatus for detection of a change of electromagnetic field in response to a gesture, to identify the gesture that caused the field change. In one instance, the apparatus may include a first conducting component having first features for the disposal on or around a portion of a user's body, to generate an electromagnetic field in response to a receipt of a source signal. The apparatus may further include a second conducting component having second features for the disposal on or around a portion of the user's body, at a distance from the first conducting component, to provide an indication of a change in the electromagnetic field over time, to identify a change of a position of the user's body portion (gesture) that causes the change in the electromagnetic field. Other embodiments may be described and/or claimed.
Abstract:
Voice activity detection technologies are disclosed. In some embodiments, the voice activity detection technologies determine whether the voice of a user of an electronic device is active based at least in part on biosignal data. Based on the determination, an audio sensor may be activated to facilitate the recording of audio signals containing audio data corresponding to an acoustic environment proximate the electronic device. The audio data may be fed to a speech recognition system to facilitate voice command operations, and/or it may be used to confirm or deny a prior determination that user voice activity is present. Device, systems, methods, and computer readable media utilizing such technologies are also described.
Abstract:
An audio processing device and method uses audio signals from a virtual rotating microphone for acoustic angle of arrival detection using a doppler effect technique.
Abstract:
Methods, apparatus, systems, and articles of manufacture for real-time voice type detection in audio data are disclosed. An example non-transitory computer-readable medium disclosed herein includes instructions, which when executed, cause one or more processors to at least identify a first vocal effort of a first audio segment of first audio data and a second vocal effort of a second audio segment of the first audio data, train a neural network including training data, the training data including the first vocal effort, the first audio segment, the second audio segment, and the second vocal effort, and deploy the neural network, the neural network to distinguish between the first vocal effort and the second vocal effort.
Abstract:
Methods, apparatus, and software for implementing dual Bayesian encoding-decoding for text-to-code transformations. In one aspect, a multi-model probabilistic source code model employing dual Bayesian encoder-decoder models is used to convert natural language (NL) inputs (aka requests) into source code. An NL input is processed to generate a Probabilistic Distribution (PD) of Source code (SC) tokens in an SC token sequence and a PD of Abstract Syntax Tree (AST) tokens in an AST token sequence, wherein each SC token is associated with a respective AST token, and each of the SC and AST tokens have a respective PD. One or more fixing rules are applied to one or more tokens SC tokens that are identified as needing fixing, wherein the fixing rule are selected in consideration of the PDs of the SC tokens and the PDs of their associated AST tokens.