Deepmind technologies limited (20240135955). GENERATING AUDIO USING NEURAL NETWORKS simplified abstract
Contents
GENERATING AUDIO USING NEURAL NETWORKS
Organization Name
Inventor(s)
Aaron Gerard Antonius Van Den Oord of London (GB)
Sander Etienne Lea Dieleman of London (GB)
Nal Emmerich Kalchbrenner of Amsterdam (NL)
GENERATING AUDIO USING NEURAL NETWORKS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240135955 titled 'GENERATING AUDIO USING NEURAL NETWORKS
Simplified Explanation: The patent application describes methods, systems, and apparatus for generating an output sequence of audio data with specific audio samples at different time steps. It involves using a convolutional subnetwork to process the current audio data sequence and an output layer to generate a score distribution over possible audio samples for each time step.
- The method involves providing a current sequence of audio data to a convolutional subnetwork for processing.
- The convolutional subnetwork generates an alternative representation for each time step.
- The alternative representation is then input to an output layer to generate a score distribution over possible audio samples for that time step.
Key Features and Innovation:
- Utilizes a convolutional subnetwork to process audio data sequences.
- Generates alternative representations for each time step.
- Uses an output layer to create a score distribution over possible audio samples.
Potential Applications: This technology can be used in speech recognition systems, music generation software, and audio processing applications.
Problems Solved: Addresses the need for efficient processing of audio data sequences and generating accurate score distributions for different time steps.
Benefits:
- Improved accuracy in audio data processing.
- Enhanced performance in generating score distributions.
- Increased efficiency in handling audio sequences.
Commercial Applications: Potential commercial applications include speech recognition software, music production tools, and audio editing programs.
Prior Art: No specific information on prior art related to this technology is provided in the abstract.
Frequently Updated Research: There is ongoing research in the field of audio data processing and neural network applications for audio analysis.
Questions about Audio Data Processing: 1. How does the convolutional subnetwork improve the processing of audio data sequences? 2. What are the potential limitations of using an output layer to generate score distributions for audio samples?
Original Abstract Submitted
methods, systems, and apparatus, including computer programs encoded on computer storage media, for generating an output sequence of audio data that comprises a respective audio sample at each of a plurality of time steps. one of the methods includes, for each of the time steps: providing a current sequence of audio data as input to a convolutional subnetwork, wherein the current sequence comprises the respective audio sample at each time step that precedes the time step in the output sequence, and wherein the convolutional subnetwork is configured to process the current sequence of audio data to generate an alternative representation for the time step; and providing the alternative representation for the time step as input to an output layer, wherein the output layer is configured to: process the alternative representation to generate an output that defines a score distribution over a plurality of possible audio samples for the time step.
