Voice Based Gender Detection on Edge for Leading Semiconductor Company in US

The client is a leading US-based semiconductor manufacturer offering microcontrollers and processors to sensors, analog ICs, and connectivity solutions. They focused on introducing a new line of chipsets designed for Machine Learning at the edge, and they sought to bring innovative applications to the market. ACL Digital designed a voice-based gender detection application. This application utilized a supervised machine learning algorithm, specifically the Depth-wise Separable Convolutional Neural Network. The model was developed using the TensorFlow framework, and the training process involved leveraging extracted features to enhance the gender detection functionality.