Time-stretch audio clips quickly with PyTorch (CUDA supported)! Additional utilities for searching efficient transformations are included.

Overview

Torch Time Stretch

Time-stretch audio clips quickly with PyTorch (CUDA supported)! Additional utilities for searching efficient transformations are included.

View on PyPI / View Documentation

Publish to PyPI Run tests PyPI version Number of downloads from PyPI per month Python version support Code Style: Black

About

This package includes two main features:

  • Time-stretch audio clips quickly using PyTorch (with CUDA support)
  • Calculate efficient time-stretch targets (useful for augmentation, where speed is more important than precise time-stretches)

Also check out torch-pitch-shift, a sister project for pitch-shifting.

Installation

pip install torch-time-stretch

Usage

Example

Check out example.py to see torch-time-stretch in action!

Documentation

See the documentation page for detailed documentation!

Contributing

Please feel free to submit issues or pull requests!

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Comments
  • RuntimeError: The size of tensor a (40264) must match the size of tensor b (173) at non-singleton dimension 1

    RuntimeError: The size of tensor a (40264) must match the size of tensor b (173) at non-singleton dimension 1

    I use same code in https://github.com/KentoNishi/torch-time-stretch/blob/master/example.py but get below error

    (librosa) āžœ  torch-time-stretch git:(master) āœ— python example.py 
    Traceback (most recent call last):
      File "/home/jackie/code/github/torch-time-stretch/example.py", line 48, in <module>
        test_time_stretch_2_up()
      File "/home/jackie/code/github/torch-time-stretch/example.py", line 20, in test_time_stretch_2_up
        up = time_stretch(sample, Fraction(1, 2), SAMPLE_RATE)
      File "/home/jackie/code/github/torch-time-stretch/torch_time_stretch/main.py", line 116, in time_stretch
        output = stretcher(output)
      File "/home/jackie/anaconda3/envs/librosa/lib/python3.9/site-packages/torch/nn/modules/module.py", line 1130, in _call_impl
        return forward_call(*input, **kwargs)
      File "/home/jackie/anaconda3/envs/librosa/lib/python3.9/site-packages/torchaudio/transforms/_transforms.py", line 1059, in forward
        return F.phase_vocoder(complex_specgrams, rate, self.phase_advance)
      File "/home/jackie/anaconda3/envs/librosa/lib/python3.9/site-packages/torchaudio/functional/functional.py", line 743, in phase_vocoder
        phase = angle_1 - angle_0 - phase_advance
    RuntimeError: The size of tensor a (40264) must match the size of tensor b (173) at non-singleton dimension 1
    
    opened by Jackiexiao 4
  • Example ratios are reversed.

    Example ratios are reversed.

    Love it, thanks for making this! Tiny thing: In the example test_time_stretch_2_up should use 1/2 as a ratio, not 2/1. test_time_stretch_2_down should use that 2/1 (it's stretching the clip length by 2x).

    opened by hdemmer 1
  • Does it with mono-channel wav files?

    Does it with mono-channel wav files?

    my audio clip is in mono 16khz audio, [ 0 0 0 ... 63 100 127], so it will throw

    ---> 15 down = time_stretch(sample, Fraction(2, 1), SAMPLE_RATE)
         16 wavfile.write(
         17     "./stretched_down_2.wav",
         18     SAMPLE_RATE,
         19     np.swapaxes(down.cpu()[0].numpy(), 0, 0).astype(dtype),
         20 )
    
    File /opt/conda/envs/classify-audio/lib/python3.9/site-packages/torch_time_stretch/main.py:108, in time_stretch(input, stretch, sample_rate, n_fft, hop_length)
        106 if not hop_length:
        107     hop_length = n_fft // 32
    --> 108 batch_size, channels, samples = input.shape
        109 # resampler = T.Resample(sample_rate, int(sample_rate / stretch)).to(input.device)
        110 output = input
    
    ValueError: not enough values to unpack (expected 3, got 2)
    
    opened by ti3x 0
Releases(v1.0.3)
Owner
Kento Nishi
17-year-old programmer at Lynbrook High School, with strong interests in AI/Machine Learning. Open source developer and researcher at the Four Eyes Lab.
Kento Nishi
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