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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