mindspore.dataset.audio
This module is to support audio augmentations. It includes two parts: transforms and utils. transforms is a high performance processing module with common audio operations. utils provides some general methods for audio processing.
Common imported modules in corresponding API examples are as follows:
import mindspore.dataset as ds
import mindspore.dataset.audio.transforms as audio
Descriptions of common data processing terms are as follows:
TensorOperation, the base class of all data processing operations implemented in C++.
AudioTensorOperation, the base class of all audio processing operations. It is a derived class of TensorOperation.
mindspore.dataset.audio.transforms
Design two-pole all-pass filter with central frequency and bandwidth for audio waveform. |
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Turn the input audio waveform from the amplitude/power scale to decibel scale. |
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Calculate the angle of complex number sequence. |
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Design two-pole band-pass filter for audio waveform. |
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Design two-pole Butterworth band-pass filter for audio waveform. |
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Design two-pole Butterworth band-reject filter for audio waveform. |
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Design a bass tone-control effect, also known as two-pole low-shelf filter for audio waveform. |
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Compute the norm of complex number sequence. |
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Apply contrast effect for audio waveform. |
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Apply masking to a spectrogram in the frequency domain. |
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Design two-pole low-pass filter for audio waveform. |
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Apply masking to a spectrogram in the time domain. |
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Stretch Short Time Fourier Transform (STFT) in time without modifying pitch for a given rate. |
mindspore.dataset.audio.utils
Scale Types. |