TinyML In Action—Creating a Voice Controlled Robotic Subsystem

With a solid foundational understanding of the concepts that underlie the field of TinyML, we’ll be applying our knowledge to a real-life project.

A note before digging into this project, I just wanted to make clear that this project will be using pre-existing datasets, Google Colabs, and Arduino code developed by both Pete Warden and the TinyML team at Harvard University. To deploy on our microcontroller unit (MCU), their resources will provide us with:

Access to datasets

Model architectures

Training scripts

Quantization scripts

Evaluation tools

Arduino code

As a disclaimer, we did not develop the vast majority of this code, and we do not own the rights to it.

All said and done, this project assumes a basic understanding of programming and electronics.

Automate Testing