Intel Corporation (20240244389). DEEP LEARNING SOLUTION FOR VIRTUAL ROTATION OF BINAURAL AUDIO SIGNALS simplified abstract
Contents
DEEP LEARNING SOLUTION FOR VIRTUAL ROTATION OF BINAURAL AUDIO SIGNALS
Organization Name
Inventor(s)
Hector Cordourier Maruri of Guadalajara (MX)
Jesus Ferrer Romero of Guadalajara (MX)
Willem Beltman of West Linn OR (US)
DEEP LEARNING SOLUTION FOR VIRTUAL ROTATION OF BINAURAL AUDIO SIGNALS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240244389 titled 'DEEP LEARNING SOLUTION FOR VIRTUAL ROTATION OF BINAURAL AUDIO SIGNALS
Simplified Explanation: This patent application describes techniques for providing binaural sound signals that adjust to match head rotation, maintaining the perceived location of audio output relative to the user as they turn their head.
Key Features and Innovation:
- Utilizes deep-learning based audio regression to generate binaural sound signals that change with head rotation.
- Extracts spherical location information embedded in binaural signals to create rotated audio output.
- Implements deep learning operations such as convolution, pooling, and nonlinear operations in a neural network for audio processing.
Potential Applications: This technology could be used in virtual reality systems, gaming, audio production, and communication devices to enhance the immersive audio experience for users.
Problems Solved: Addresses the challenge of maintaining audio localization in headphones when users rotate their heads, improving the realism and accuracy of spatial audio perception.
Benefits:
- Enhanced user experience in virtual environments.
- Improved spatial audio accuracy and realism.
- Seamless audio localization with head movement.
Commercial Applications: Potential commercial applications include virtual reality headsets, gaming peripherals, audio editing software, and communication devices with spatial audio capabilities.
Prior Art: Researchers and developers in the fields of virtual reality, audio processing, and neural networks may have explored similar techniques for spatial audio processing and binaural sound manipulation.
Frequently Updated Research: Stay informed about advancements in deep learning algorithms for audio processing, spatial audio technologies, and applications of neural networks in virtual reality and gaming industries.
Questions about Binaural Sound Rotation: 1. How does this technology improve the user experience in virtual reality environments? 2. What are the key components of the deep-learning based audio regression method used in this innovation?
Original Abstract Submitted
techniques are provided herein for providing binaural sound signals that are virtually rotated to match head rotation, such that audio output to headphones is perceived to maintain its location relative to user when a user turns their head. in particular, techniques are presented to extract spherical location information already embedded in binaural signals to generate binaural sound signals that change to match head rotation. a deep-learning based audio regression method can use a 2-channel binaural audio signal and a rotation angle as input, and generate a new binaural audio output signal with the rotated environment corresponding to the rotation angle. the deep-learning based audio regression method can be implemented as a neural network, and can include deep learning operations, such as convolution, pooling, elementwise operation, linear operation, and nonlinear operation. a deep learning operation may be performed on internal parameters of the dnns and one or more activations.
