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US 12,763,084 B2Granted
Deep learning segmentation of audio using magnitude spectrogram
AssigneeAudioshake, Inc.
InventorLuke Miner
Life of this patent
Estimating the term…
Abstract
A method, system, and computer readable medium for decomposing an audio signal into different isolated sources. The techniques and mechanisms convert an audio signal into K input spectrogram fragments. The fragments are sent into a deep neural network to isolate for different sources. The isolated fragments are then combined to form full isolated source audio signals.
Claims20
A method for decomposing an audio signal, the method comprising:
- transforming an original audio file into a complex spectrogram;
- splitting the complex spectrogram into K small fragments along the time dimension;
- sending each fragment in the K small fragments through one or more convolutional deep neural networks, the convolutional deep neural networks including one or more convolutional layers, the one or more convolutional layers including a subpixel upsample convolutional layer;
- producing a sequence of K mask fragments, wherein the K mask fragments are used to extract individual components from the original audio file;
- multiplying the K mask fragments with the complex spectrogram to create a new complex spectrogram;
- and
- transforming the new complex spectrogram into a new audio file associated with a decomposed audio signal.
4 more elements
A system for decomposing an audio signal, the system comprising:
- a processor;
- and
- memory storing instructions to cause the processor to execute a method, the method comprising:
- transforming an original audio file into a complex spectrogram;
- splitting the complex spectrogram into K small fragments along the time dimension;
- sending each fragment in the K small fragments through one or more convolutional deep neural networks, the convolutional deep neural networks including one or more convolutional layers, the one or more convolutional layers including a subpixel upsample convolutional layer;
- producing a sequence of K mask fragments, wherein the K mask fragments are used to extract individual components from the original audio file;
- multiplying the K mask fragments with the complex spectrogram to create a new complex spectrogram;
- and
- transforming the new complex spectrogram into a new audio file.
7 more elements
A non-transitory computer readable medium storing instructions to cause a processor to execute a method, the method comprising:
- transforming an original audio file into a complex spectrogram;
- splitting the complex spectrogram into K small fragments along the time dimension;
- sending each fragment in the K small fragments through one or more convolutional deep neural networks, the convolutional deep neural networks including one or more convolutional layers, the one or more convolutional layers including a subpixel upsample convolutional layer;
- producing a sequence of K mask fragments, wherein the K mask fragments are used to extract individual components from the original audio file;
- multiplying the K mask fragments with the complex spectrogram to create a new complex spectrogram;
- and
- transforming the new complex spectrogram into a new audio file.
4 more elements
Dependencies are inferred from the claim text.