Building Intelligent Audio Systems- Audio Feature Extraction using Machine Learning

Given the recent trends in machine learning and deep learning, we have tried to give a high-level overview of how digital signal processing, machine learning, and deep learning algorithms can go hand-in-hand to categorize or draw inferences from audio signals. Audio-specific neural network models can also be built using signal processing, machine learning, and deep learning (neural networks) algorithms. In this blog will see how to build Intelligent Audio Systems, Audio Feature Extraction using Machine Learning.

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Rhishikesh Agashe

Rhishikesh Agashe holds nearly 19 years of experience in the IT Industry. 4 years as an Entrepreneur and 15 years in the Embedded domain wherein most of his experience was in Embedded Media Processing where he was involved in Implementation of Audio and Speech Algorithms on various Microprocessors/DSPs(ARM/MIPS/TI/CRADLE/CevaDSP/Meta). He holds a Bachelor of Engineering (BE) Degree in Electronics and Telecommunications and carries a strong entrepreneurship potential within. Rhishikesh Agashe is also a Debutante Author.

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