Project DetailsThe project "Speaker Training" focuses on developing a system for ranking speakers based on audio recordings. The goal is to create a neural network that can identify and rank different speakers based on acoustic features, using the TEDLIUM dataset. This dataset contains recordings from various speakers in different languages, allowing the network to learn the unique characteristics of each speaker. The process includes stages of audio signal processing, extracting features such as frequency parameters, speech rate, and other acoustic traits, followed by training the neural network to identify the speaker and provide a ranking. The system aims to improve ranking accuracy through advanced machine learning techniques.
