Building a Music Genre Recognition Application with TinyML on Raspberry Pi Pico

Join a technical talk where Arm's Machine Learning Group Team Lead, Gian Marco Iodice, demonstrates building a music genre recognition application for the Raspberry Pi Pico. Learn how to implement TensorFlow Lite for Microcontrollers and CMSIS-DSP library while exploring the influence of target device constraints on machine learning model deployment. Discover techniques for optimizing Mel-frequency cepstral coefficients (MFCCs) feature extraction using fixed-point arithmetic to enhance latency performance. Explore the design considerations behind implementing a long-short-term memory (LSTM) recurrent neural network (RNN) for music genre classification. Follow along with the step-by-step deployment process on the Raspberry Pi Pico, gaining practical insights into embedded machine learning development. Participate in a book giveaway opportunity to win a free copy of the TinyML Cookbook's second edition.