This Arduino device can detect which language is being spoken using tinyML
Although smartphone users have had the ability to quickly translate spoken words into nearly any modern language for years now, this feat has been quite tough to accomplish on small, memory-constrained microcontrollers. In response to this challenge, Hackster.io user Enzo decided to create a proof-of-concept project that demonstrated how an embedded device can determine the language currently being spoken without the need for an Internet connection.
This so-called “language detector” is based on an Arduino Nano 33 BLE Sense, which is connected to a common PCA9685 motor driver that is, in turn, attached to a set of three micro servo motors — all powered by a single 9V battery. Enzo created a dataset by recording three words: “oui” (French), “si” (Italian), and “yes” (English) for around 10 minutes each for a total of 30 minutes of sound files. He also added three minutes of random background noise to help distinguish between the target keywords and non-important words.
Once a model had been trained using Edge Impulse, Enzo exported it back onto his Nano 33 BLE Sense and wrote a small bit of code that reads audio from the microphone, classifies it, and determines which word is being spoken. Based on the result, the corresponding nation’s flag is raised to indicate the language.
You can see the project in action below and read more about it here on Hackster.io.