Deep Learning Approaches for Speech Recognition Systems

This project aims to develop an efficient speech recognition system using deep learning techniques to identify and differentiate between multiple speakers. Voice recordings from various users, such as User1, User2, and User3, are collected to form a comprehensive dataset for training the model. By leveraging deep neural networks, the system learns distinct vocal characteristics and patterns unique to each individual, enabling accurate speaker recognition. After training, the model is tested to assess its performance in real-time speaker identification scenarios. This deep learning-based approach enhances the accuracy and reliability of speech recognition systems, making it suitable for applications such as voice authentication, personalized virtual assistants, and security verification.