EchoFree : AI Powered Audio Clenaer

This paper presented EchoFree, an AI-powered audio enhancement system designed to improve the quality of pre-recorded audio by effectively reducing noise while preserving speech clarity and naturalness. The proposed system utilizes a hybrid deep learning approach that combines a pretrained speech enhancement model with a custom autoencoder, enabling efficient noise suppression and accurate reconstruction of clean speech signals. By operating in the time-frequency domain using Short-Time Fourier Transform (STFT), the system is able to capture important audio features and perform effective separation of speech and noise components. The experimental results demonstrate that EchoFree significantly improves speech intelligibility, perceptual quality, and overall audio clarity across various noise conditions such as background noise, echo, and environmental disturbances. The system achieves better performance compared to traditional signal processing techniques and single-model approaches, providing more stable and consistent results. Additionally, the modular design and web- based implementation make the system scalable, user-friendly, and suitable for real-world applications.   Overall, EchoFree provides a robust, efficient, and practical solution for audio enhancement, contributing to the advancement of intelligent speech processing systems. The proposed approach highlights the effectiveness of combining signal processing with deep learning techniques to address real-world challenges in speech enhancement.

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