New Technique for Recursive Least Square Adaptive Algorithm for Acoustic Echo Cancellation of Speech signal in an auditorium

In today’s technological society, human computer interactions are ever increasing. In many new systems, voice recognition platforms are implemented to give users more convenient ways of operating equipment and systems. To improve the audibility of the speech, the noise and acoustic echo must be removed from the speech signal. In this paper, we presented a new adaptive algorithm in the frequency domain for acoustic echo cancellation of speech signal in an auditorium. The RLS algorithm, the forgetting factor remains constant, which is utilized for the stability of the adaptive algorithm. However, the constant value of the forgetting factor will not support for the sensitive system. The value of the forgetting factor depends on the echo and reverberation. In an auditorium speech, the echo and reverberation signals are not in a stable manner since the constant value of forgetting factor is not a perfect solution for the removing the echo and reverberation. In order to solve this problem we presented average recursive least square adaptive algorithm, which produces the flexible forgetting factor in a min-max manner. The estimated echo values are constructed with the aid of combined feature of the minmax manner, which leads to increase the quality of the speech signal. Finally, our proposed algorithm is implemented using MATLAB and the experimental results showed that the proposed ARLS algorithm outperformed than the existing RLS algorithm.