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You're reading from  TinyML Cookbook - Second Edition

Product typeBook
Published inNov 2023
PublisherPackt
ISBN-139781837637362
Edition2nd Edition
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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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Acquiring audio data with the Arduino Nano

Building the dataset with recordings obtained with the mobile phone’s microphone is undoubtedly good enough for many applications. However, to prevent any potential loss in accuracy during the model’s deployment, we should also include audio clips recorded with the microphone used by the end application in the dataset.

Therefore, this recipe will show you how to record audio samples with the built-in microphone on the Arduino Nano through Edge Impulse.

Getting ready

In the previous recipe, you will have noticed that in the options reported in the Collect data section, the mobile phone was not the only one, as shown in the following screenshot:

Figure 4.9: Some of the options available to collect data in Edge Impulse

For example, as reported in the previous screenshot, you can collect data using your computer’s microphone or a fully supported microcontroller board.

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TinyML Cookbook - Second Edition
Published in: Nov 2023Publisher: PacktISBN-13: 9781837637362

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