Design and Implementation of Echo Detection and Cancellation Algorithms in LABVIEW

Echo cancellation and detection play a crucial role in ensuring clear speech transmission in various communication applications. Traditional methods rely on adaptive filtering techniques, but their performance is often limited in dynamic environments with varying acoustic conditions. To address this limitation, we propose a novel Adaptive Echo Cancellation and Detection Framework (AECD) using LabVIEW. This framework integrates adaptive signal processing with real-time noise estimation, enabling robust suppression of echo artifacts while preserving speech integrity. The system utilizes real-time audio acquisition and employs frequency-domain analysis to identify and mitigate echo signals effectively. Extensive evaluations on controlled and real-world datasets demonstrate the efficiency of our approach. For instance, in a teleconferencing environment with high reverberation, AECD achieves a 30% reduction in residual echo compared to conventional adaptive filters. Similarly, in hands-free communication scenarios, our method improves speech clarity by 25%, as measured by objective intelligibility metrics. These results highlight the superior performance of AECD in diverse acoustic conditions, making it a valuable solution for telecommunications, video conferencing, and hands-free communication systems. This study underscores the potential of LabVIEW in implementing real-time echo cancellation, paving the way for advancements in speech enhancement and acoustic signal processing.