In modern telecommunication systems like hands-free and teleconferencing systems, the problem arise during conversation is the creation of an acoustic echo. This problem degrades the quality of the information signal. All speech processing equipments like noise cancelling headphones and hearing aids should be able to filter different kinds of interfering signals and produce a clear sound to the listener. Currently, echo cancellation is a most interesting and challenging task in any communication system. Echo is the delayed and degraded version of original signal which travels back to its source after several reflections. Eliminating this effect without affecting the original quality of the speech is a challenge of research in present days. Echo cancellation in voice communication is a process of removing the echo to improve the clarity and quality of the voice signals. In our thesis we mainly focused on the acoustic echo cancellation in a closed room using adaptive filters. The Acoustic echo cancellation with adaptive filtering technique will more accurately enhance the speech quality in hands free communication systems. The main aim of using adaptive algorithms for echo cancellation is to achieve higher ERLE at higher rate of convergence with low complexity. The adaptive algorithms NLMS, APA and RLS are implemented using MATLAB. These algorithms are tested with the simulation of echo occurring environment by using constant room dimensions , microphone and source positions. The performance of the NLMS, APA and RLS are evaluated in terms ERLE and misalignment. The results show that RLS algorithm achieve good performance with more computational complexity comparing with the NLMS and APA algorithms. The NLMS algorithm has very low computational complexity comparing to RLS and APA algorithms. The results are taken for both input signal as speech signal and noise separately and plotted in the results section.