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  1. Audio

Basics

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Last updated 1 year ago

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Series by ketan Doshi

  1. (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. (Processing audio data in Python. What are Mel Spectrograms and how to generate them)

  3. (Enhance Spectrograms features for optimal performance by hyper-parameter tuning and data augmentation)

  4. (End-to-end example and architecture to classify ordinary sounds. Foundational application for a range of scenarios.)

  5. (Speech-to-Text algorithm and architecture, using CTC Loss and Decoding for aligning sequences.)

  6. (Algorithm commonly used by Speech-to-Text and NLP applications to enhance predictions)

State-of-the-Art Techniques
Why Mel Spectrograms perform better
Data Preparation and Augmentation
Sound Classification
Automatic Speech Recognition
Beam Search