• Rutik Namdeo Rathod
• Sopan Nagorao Waghmare
• Pooja Mahadev survase
• Aishwarya Jagatsing Gaherwar
• Swapnali R. Bhujbal

Object We are going to build an embedded application that uses an 18 KB model, trained on a dataset of speech commands, to classify spoken audio. The model is trained to recognize the words "yes" and "no,' and is also capable of distinguishing between unknown words and silence or background noise. Our application will listen to its surroundings with a microphone and indicate when it has detected a word by lighting an LED or displaying data on a screen, depend it on the capabilities of the device. Understanding this code will give you the ability to control any electronics project with voice commands.

ESP EYE, SPECTOGRAM, EASE, LOW POWER CONSUMPTION, SCALABILITY, ETC.

"Speech Recognition Using Tiny ML", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 5, page no.g452-g456, May-2023, Available :http://www.jetir.org/papers/JETIR2305667.pdf

"Speech Recognition Using Tiny ML", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 5, page no. ppg452-g456, May-2023, Available at : http://www.jetir.org/papers/JETIR2305667.pdf