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You're reading from  TinyML Cookbook - Second Edition

Product typeBook
Published inNov 2023
PublisherPackt
ISBN-139781837637362
Edition2nd Edition
Concepts
Machine Learning
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Author (1)
Gian Marco Iodice
Gian Marco Iodice
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Gian Marco Iodice

Gian Marco Iodice is team and tech lead in the Machine Learning Group at Arm, who co-created the Arm Compute Library in 2017. The Arm Compute Library is currently the most performant library for ML on Arm, and it's deployed on billions of devices worldwide – from servers to smartphones. Gian Marco holds an MSc degree, with honors, in electronic engineering from the University of Pisa (Italy) and has several years of experience developing ML and computer vision algorithms on edge devices. Now, he's leading the ML performance optimization on Arm Mali GPUs. In 2020, Gian Marco cofounded the TinyML UK meetup group to encourage knowledge-sharing, educate, and inspire the next generation of ML developers on tiny and power-efficient devices.
Read more about Gian Marco Iodice

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Deploying the MFCCs feature extraction algorithm on the Raspberry Pi Pico

The final two recipes of this chapter will guide us through the development of the music genre classification application on the microcontroller.

In this particular recipe, we will deploy the MFCCs feature extraction algorithm using the CMSIS-DSP on the Raspberry Pi Pico.

Getting ready

Extracting MFCCs from raw audio data is the first stage of our computing chain to classify music genres. Since we developed this algorithm in Python using the CMSIS-DSP library, transitioning to a C language implementation should be relatively straightforward.

The C version of the CMSIS-DSP library mirrors its Python counterpart, offering the same functions and, often, an identical API, simplifying the migration to the final implementation on a board.

The only ingredients needed to deploy the MFCCs feature extraction algorithm on the Raspberry Pi Pico or other Arm-based microcontrollers are the following:

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TinyML Cookbook - Second Edition
Published in: Nov 2023Publisher: PacktISBN-13: 9781837637362
© 2023 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Gian Marco Iodice

Gian Marco Iodice is team and tech lead in the Machine Learning Group at Arm, who co-created the Arm Compute Library in 2017. The Arm Compute Library is currently the most performant library for ML on Arm, and it's deployed on billions of devices worldwide – from servers to smartphones. Gian Marco holds an MSc degree, with honors, in electronic engineering from the University of Pisa (Italy) and has several years of experience developing ML and computer vision algorithms on edge devices. Now, he's leading the ML performance optimization on Arm Mali GPUs. In 2020, Gian Marco cofounded the TinyML UK meetup group to encourage knowledge-sharing, educate, and inspire the next generation of ML developers on tiny and power-efficient devices.
Read more about Gian Marco Iodice

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