Voice-Sex Recognition Classifier (2019)

Developed a classifier to recognize the sex of a speaker in audio recordings by analyzing various voice features. The project used neural networks and other machine learning models to find patterns in the data. The implementation was carried out in Python and R, using libraries such as TensorFlow, Keras, and Sklearn.

The process involved data preprocessing, feature engineering, model development, and evaluation to achieve accurate predictions. You can find the code here.