Audio Classification

1. 1
   Mel-Spectrogram Feature Extraction

   Extract mel-spectrogram features from audio files using Librosa. Visualize the spectrogram and understand its parameters.
2. 2
   Training with Audio-Specific Transformers (AST)

   Train an Audio Spectrogram Transformer (AST) model for audio classification using PyTorch. Prepare your dataset and fine-tune the pre-trained AST model.
3. 3
   Zero-Shot Audio Classification with CLAP

   Perform zero-shot audio classification using the CLAP model. Encode audio and text descriptions, then calculate similarity scores to classify audio without training.

Start by extracting mel-spectrogram features from a sample audio file. Then, explore pre-trained audio classification models like AST and CLAP.

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