Additional spectral feature transformations
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- Dominant language
- Python
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Description
While torchaudio provides a Mel-scaled spectrogram transformation (torchaudio.transforms.MEL), there’re a few additional spectral feature transformations that are extremely useful for pre-processing and data augmentation. For example, two feature transformations that I’d love to see in torchaudio are
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by reviewing the existing torchaudio.transforms.MEL transformation and the linked CENS chromagrams reference. Determine the expected CENS transformation behavior and how it fits the current audio preprocessing and data augmentation APIs. Done means the requested CENS chromagram transformation is available in torchaudio and behaves consistently with the reference.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- audio-video-rtc
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100