Audio Classification

Learn to classify audio using machine learning, covering feature extraction, audio-specific transformers, and zero-shot classification.

audioclassificationsound-event-detectionenvironmental-audioanomaly-detectionmachine-learningpytorchtransformerszero-shot

3 Steps

1
Mel-Spectrogram Feature Extraction: Extract mel-spectrogram features from audio files using Librosa. Visualize the spectrogram and understand its parameters.
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
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.

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