CHeggan/MetaAudio-A-Few-Shot-Audio-Classification-Benchmark
A new comprehensive and diverse few-shot acoustic classification benchmark.
This project offers a comprehensive set of benchmarks and tools for classifying different types of audio with very limited examples. You can input various audio datasets and utilize established few-shot learning algorithms to categorize sounds even when you only have a handful of samples per category. Researchers in machine learning and audio processing who are developing new techniques for low-resource audio classification will find this useful.
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Use this if you are a researcher developing or evaluating machine learning models for audio classification and need a standardized way to test their performance when only a few labeled examples are available.
Not ideal if you are an end-user looking for a ready-to-use application to classify audio without needing to understand or implement machine learning models.
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Python
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Last pushed
Sep 22, 2024
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