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Audio Deep Learning Made Simple: Sound Classification, Step-by-Step | by Ketan Doshi | Towards Data Science

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Sound Classification is one of the most widely used applications in Audio Deep Learning. It involves learning to classify sounds and to predict the category of that sound. This type of problem can be applied to many practical scenarios e.g. classifying music clips to identify the genre of the music, or classifying short utterances by a set of speakers to identify the speaker based on the voice. In this article, we will walk through a simple demo application so as to understand the approach used to solve such audio classification problems. My goal throughout will be to understand not just how something works but why it works that way. I have a few more articles in my audio deep learning series that you might find useful. They explore other fascinating topics in this space including how we prepare audio data for deep learning, why we use Mel Spectrograms for deep learning models and how they are generated and optimized. Just like classifying hand-written digits using the MNIST dataset is

Audio Deep Learning Made Simple: Sound Classification, step-by-step | Towards Data Science Skip to content Artificial Intelligence Audio Deep Learning Made Simple: Sound Classification, step-by-step An end-to-end example and architecture for Audio Deep Learning's foundational application scenario, in Plain English. Ketan Doshi Mar 18, 2021 14 min read Share Hands-on Tutorials , INTUITIVE AUDIO DEEP LEARNING SERIES Photo by bruce mars on Unsplash Sound Classification is one of the most widely used applications in Audio Deep Learning. It involves learning to classify sounds and to predict t

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