habla-liaa/encodecmae
Codebase for the paper 'EncodecMAE: Leveraging neural codecs for universal audio representation learning'
This is a feature extractor designed for researchers and machine learning engineers working with audio data. It takes raw audio files as input and outputs a structured set of features (embeddings) that represent the audio's content. These embeddings can then be used for various downstream tasks like audio classification or similarity search, making it easier to analyze and understand complex audio patterns.
101 stars. No commits in the last 6 months.
Use this if you need to transform raw audio into meaningful, numerical representations for machine learning models, especially if you're exploring universal audio representation learning.
Not ideal if you primarily need to manipulate or generate audio waveforms directly without an intermediate feature extraction step.
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101
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Language
Python
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Last pushed
Jul 24, 2024
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