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Machine & Deep Learning Compendium
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Deep Neural Audio

  1. 1.
    Audio deep learning made simple by Ketan Doshi
    1. 1.
      ​State-of-the-Art Techniques (What is sound and how it is digitized. What problems is audio deep learning solving in our daily lives. What are Spectrograms and why they are all-important.)
    2. 2.
      ​Why Mel Spectrograms perform better (Processing audio data in Python. What are Mel Spectrograms and how to generate them)
    3. 3.
      ​Data Preparation and Augmentation (Enhance Spectrograms features for optimal performance by hyper-parameter tuning and data augmentation)
    4. 4.
      ​Sound Classification (End-to-end example and architecture to classify ordinary sounds. Foundational application for a range of scenarios.)
    5. 5.
      ​Beam Search (Algorithm commonly used by Speech-to-Text and NLP applications to enhance predictions)
  2. 2.
    Wav2Vec - paper Youtube​
  3. 3.
    ​Whisper
    1. 1.
      ​ZAC (Zero-shot Audio Classification using Whisper) allows you to assign audio files to ANY class you want without training.
Audio - Previous
Feature Engineering
Next - Audio
Algorithms
Last modified 1mo ago