Intel Corporation

Intel Coproration

Paulo Lopez Meyer

Hector A Cordourier Maruri

Jose Rodrigo Camacho Perez

Julio Cesar Zamora Esquivel

Alejandro Ibarra Von Borstel

Jonathan J Huang

Jesus Cruz Vargas

Willem M Beltman

Ignacio Javier Alvarez

Adam Kupryjanow

Hector Cordourier Maruri

Miguel Bernal Marin

Abraham Duenas De La Cruz

Gokcen Cilingir

David Gomez Gutierrez

Rafael De La Guardia Gonzalez

Jose I Parra Vilchis

Leobardo E Campos Macias

Rodrigo Aldana Lopez

Cagri Tanriover

David Pearce

Asli Arslan Esme

Suhel Jaber

Nese Alyuz Civitci

Hector Raul Moncada Gonzalez

Mario Alfredo Carrillo Arevalo

Giuseppe Beppe Raffa

Omesh Tickoo

David Israel Gonzalez Aguirre

Javier Felip Leon

Anthony George LaMarca

Marcos Emanuel Carranza

Javier Sebastian Turek

David Arditti Ilitzky

Mateo Guzman

Cesar Martinez-Spessot

Xiaoyun May Wu

Jason A Mix

Dario Oliver

Julio Zamora Esquivel

Karol Duzinkiewicz

Carlos A Flores Fajardo

Jorge Romero Aragon

Carlos Alberto Lopez Perez

Mario Alfredo C Arevalo

Francisco Rangel Patino

Edgar Andrei Vega

Andres Viveros Wacher

Hector Cordourier

Jose Torres Ortega

Jesus Adan Cruz Vargas

An example apparatus including processor circuitry to execute instructions to join a video conferencing meeting including a first audio channel, the first audio channel including first binaural audio at a first angle; in response to a user joining a second audio channel in the video conferencing meeting, select a second angle for the second audio channel and a third angle for the first audio channel; generate a superimposed binaural audio including second binaural audio and third binaural audio; and output the superimposed binaural audio such that first audio data from the first audio channel included in the third binaural audio is to appear to originate from a first position based on the third angle and second audio data from the second audio channel included in the second binaural audio is to appear to originate from a second position based on the second angle.

Methods and apparatus to enable private verbal side conversations in virtual meetings

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.

Audio processing device and method for acoustic angle of arrival detection using audio signals of a virtual rotating microphone

Methods and apparatuses for implementing a neural network using symmetric tensors. In embodiments, a system may include a higher order neural network with a plurality of layers that includes an input layer, one or more hidden layers, and an output layer. Each of the input layer, the one or more hidden layers, and the output layer includes a plurality of neurons, where the plurality of neurons includes at least first order neurons and second order neurons, and where inputs at a second order neuron are combined using a symmetric tensor.

Multi-layer neural networks using symmetric tensors

Methods, apparatus, systems, and articles of manufacture are disclosed to enhance and audio signal. An example apparatus includes processor circuitry to at least determine a first signal spectrum corresponding to a first microphone, the first signal spectrum identifying first audio, determine a second signal spectrum corresponding to a second microphone, the second signal spectrum identifying the first audio, the second spectrum different from the first spectrum, the first microphone different from the second microphone, the second signal spectrum having a first spectral distance to the first signal spectrum, calculate a mask based on the first and second signal spectrums, and generate a third signal spectrum corresponding to the first microphone utilizing the mask and the first signal spectrum, the third signal spectrum different from the first signal spectrum, the third signal spectrum having a second spectral distance to the second signal spectrum, the second spectral distance less than the first spectral distance.

Methods and apparatus to enhance an audio signal

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.

Methods and apparatus to detect the location of sound sources external to computing devices

Systems, apparatuses and methods may provide for technology that adjusts a plurality of weights in a neural network model and adjusts a plurality of activation functions in the neural network model. The technology may also output the neural network model in response to one or more conditions being satisfied by the plurality of weights and the plurality of activation functions. In one example, two or more of the activation functions are different from one another and the activation functions are adjusted on a per neuron basis.

Artificial neural network with trainable activation functions and fractional derivative values

Hearing protection and communication apparatus using vibration sensors are disclosed. An example wearable electronic device includes means for transducing vibrations associated with speech into a first signal; means for transducing sound associated with ambient noise into a second signal; and means for processing to cause a speaker to output a signal to reduce the ambient noise; detect an identifier in the speech; and cause audio data representative of the speech to be transmitted to a second device associated with the identifier.

Hearing protection and communication apparatus using vibration sensors

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.

Lightweight full 360 audio source location detection with two microphones

A component of an Autonomous Vehicle (AV) system, the component having at least one processor; and a non-transitory computer-readable storage medium including instructions that, when executed by the at least one processor, cause the at least one processor to decode data encoded in a signal, wherein the data identifies a pattern of protrusions embedded in a driving surface, the signal being received from at least one vehicle sensor resulting from a vehicle driving over the pattern of protrusions in the driving surface.

Driving surface protrusion pattern detection for autonomous vehicles

A disclosed example includes providing vibration information to a model, the vibration information corresponding to a first vibration measured at a first mobile device when the first mobile device is in a state of non-use by a user, the model based on a plurality of vibration patterns that correspond to second vibrations measured by second mobile devices in different environments; identifying, using the model, one of the vibration patterns that corresponds to the vibration information; determining an environment of the first mobile device based on the one of the vibration patterns; and instructing the first mobile device to modify a functionality of the first mobile device based on the environment.

Surface detection for mobile devices

Techniques are disclosed to use existing vehicle speakers alone or in conjunction with other sensors (e.g. SRS sensors and/or microphones) that may already be implemented as part of the vehicle to identify acoustic signatures. Suitable low-cost and widely available hardware components (e.g., relays) may be used to modify the vehicle's existing speakers for a bi-directional mode of operation. Moreover, the vehicle's existing of audio amplifiers may be used to amplify signals collected by the speakers when operating in 'reverse,' and process these collected signals to determine vehicle state information.

In-cabin acoustic-based passenger occupancy and situation state assessment

A system, article, and method of acoustic angle of arrival detection uses both same-time and delayed-time audio signal value comparisons in a time domain that are input to a classifier neural network.

Method and system of acoustic angle of arrival detection

An apparatus for autonomous vehicles includes a perception pipeline having independent classification processes operating in parallel to respectively identify objects based on sensor data flows from multiple ones of a plurality of sensors. The apparatus also includes a sensor monitoring stage to operate in parallel with the perception pipeline and to use the sensor data flows to estimate and track a confidence level of each of the plurality of different sensors, and nullify a deficient sensor when the confidence level associated with the deficient sensor fails to meet a confidence threshold.

Multimodal sensing in autonomous driving vehicles with self-healing capabilities

Systems, apparatuses and methods may provide for origination camera technology that extracts data from multimodal sensor signals associated with a scene and generates a five-dimensional (5D) representation of the scene, wherein the 5D representation includes a three-dimensional (3D) visual representation, a one-dimensional (1D) temporal representation, and a 1D branch representation. The technology may also store the 5D representation as a set of abstract descriptors.

Artificial imagination engine using 5D information descriptors

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Zapopan, Mexico

Paulo Lopez Meyer