Intel Corporation

North Corporation

Apple Inc.

Jose Rodrigo Camacho Perez

Paulo Lopez Meyer

Hector A Cordourier Maruri

Julio Cesar Zamora Esquivel

Alejandro Ibarra Von Borstel

Jesus Cruz Vargas

Jonathan J Huang

Aycan Erentok

Willem M Beltman

Seong-Youp Suh

Hector Cordourier Maruri

Brian Girvin

Shuhei Yamada

Paul Beaucourt

Miguel Bernal Marin

Abraham Duenas De La Cruz

Shahrnaz Azizi

Ignacio Javier Alvarez

Debabani Choudhury

Bryce D Horine

David Gomez Gutierrez

Rafael De La Guardia Gonzalez

Jose I Parra Vilchis

Leobardo E Campos Macias

Rodrigo Aldana Lopez

John Groff

Eduardo Alban

Huan-Sheng Hwang

Thomas H Liu

Hector Raul Moncada Gonzalez

Mario Alfredo Carrillo Arevalo

Omesh Tickoo

David Israel Gonzalez Aguirre

Harry G Skinner

Javier Felip Leon

Assaf Gurevitz

Marcos Emanuel Carranza

Oner Orhan

Javier Sebastian Turek

Jie Gao

David Arditti Ilitzky

Amir Israel Rubin

Vinod Kristem

Shlomi Vituri

Tae Young Yang

Adam Kupryjanow

Cesar Martinez-Spessot

Mateo Guzman

Jason A Mix

Dario Oliver

Julio Zamora Esquivel

Janardhan Koratikere Narayan

Alberto Alcocer Ochoa

Timo Huusari

Vida Ilderem Burger

Ivan Simoes Gaspar

Karol Duzinkiewicz

Tae-Young Yang

Jorge Romero Aragon

Andres Viveros Wacher

Edgar Andrei Vega

Francisco Rangel Patino

Mario Alfredo C Arevalo

Carlos Alberto Lopez Perez

Amer Al-baidhani

Jose Torres Ortega

Timo Sakari Huusari

Jesus Adan Cruz Vargas

This disclosure describes systems, methods, and devices related to reducing noise in and improving speech signals and radio signals. A device may identify a radio frequency signal received by radio frequency circuity at a time; apply a Short Time Fourier Transform (STFT) to the radio frequency signal to generate a STFT signal; identify a signal-to-noise ratio associated with the radio frequency signal at the time; identify a packet-error-rate associated with the radio frequency signal at the time; identify activity when the multiplexed radio frequency signal is received by the radio frequency circuity at the time; select, based on the signal-to-noise ratio, the packet-error-rate, and the activity, a spectral mask to be applied to the STFT signal; apply the selected spectral mask to the STFT signal to generate a clean STFT signal; and apply an inverse STFT to the clean STFT signal to generate a clean radio frequency signal.

Single device for noise mitigation and enhancement of speech and radio signals

A radio frequency front end and an antenna front end may be separated from one another to maintain close proximity between a low noise amplifier and an antenna while achieving improved thermal regulation of a power amplifier. The radio frequency front end and antenna front end may include a duplexing system that enables operation with a single electrical cable. Furthermore, where it is desired to transmit a radiofrequency signal via a waveguide, a flexible waveguide may be constructed with a distributed capacitance between waveguide protrusions.

Antenna duplexing, waveguides, and methods thereof

Various antennas elements including antennas arrays can support various communication technologies and can be integrated into different components or subcomponents of a vehicle, including various vehicle light assemblies. The vehicular antennas elements include low profile and/or concealed antenna elements that are inconspicuous aesthetically and do not affect or substantially affect vehicle aerodynamics.

Embedded antennas structures for wireless communications and radar

A method and apparatus to estimate and mitigate platform noise incurred at a wireless device coupled to the platform. A computing device includes a platform including a first processor, a wireless device coupled to the platform, the wireless device including a second processor, and a plurality of antennas coupled to the wireless device. At least one of the first processor or the second processor is configured to determine characteristics of a platform noise incurred at the wireless device in real-time due to utilization of circuitries and processing components on the platform and implement an adaptive real-time and application/context-aware measure to mitigate the platform noise based on the determined characteristics of the platform noise.

Method and apparatus to mitigate platform noise and interference incurred at a wireless device coupled to the platform

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

Monodirectional antennas may be arranged to radiate in a near omni-directional pattern. By incorporating switches into the antenna arrangement, the antennas can be controlled to selectively radiate from a common radiofrequency feed. These arrangements may be packaged in a housing, which may aid both in antenna performance and in antenna installation. According to another aspect of the disclosure, housings may include a plurality of antennas, and one or more procedures may be implemented to determine a codebook to radiate from the circular arrangement according to various beam constrains.

Antenna units, radiation and beam shape of antenna units, and methods thereof

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

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

Growing community of inventors

Guadalajara Jalisco, Mexico

Jose Rodrigo Camacho Perez