Wolfram Language

Net Encoders for Audio

A variety of audio-specific NetEncoder objects are now available to help solidly integrate the Audio object with the neural net framework. The encoders are a key part of the framework, since they provide an easy way to inject data into a neural net.

Inspect the features from each encoder computed on a recording of a bird.

The "Audio" net encoder simply returns the waveform after a resampling and downmixing step.

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The "AudioSTFT" net encoder computes the Fourier transform on partitions of the input signal. This feature contains both time and frequency information.

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The "AudioSpectrogram" net encoder returns the power spectrum computed on partitions of the input signal.

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The "AudioMelSpectrogram" net encoder returns a spectrogram that has been filtered so that the frequency bins are nonlinearly spaced to mimic the pitch perception in humans.

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The "AudioMFCC" net encoder performs some further dimensionality reduction on the mel spectrogram, while preserving most of the information contained in the signal.

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Related Examples

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