Adaptive signal processing
Adaptive filter theory (3rd ed.)
Adaptive filter theory (3rd ed.)
Adaptive echo cancellation using least mean mixed-norm algorithm
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
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The telecommunications sector is characterized by an increasing demand for user friendliness and interactivity. This shows the growing interest in hands-free communication systems. Hands-free communication ensures communication without any physical contact with either a microphone or a loudspeaker. Signal quality in current hands-free systems is unsatisfactory due to the acoustic echo. Echo cancellation plays a vital role in improving the quality and intelligibility of speech. Acoustic echo cancellation is important in acoustically coupled environments, where the signal generated by a loudspeaker is fed back into a microphone, thus disrupting the signal that the microphone originally intended to receive. To overcome this, many advanced signal processing techniques have been used. This paper focuses on the use of adaptive filtering techniques to reduce this unwanted echo, thus increasing speech quality. These techniques are known to have computationally efficient solutions. In Adaptive filters the weights of the filter are adjusted in order to reduce the error. This adaptation of weights can be achieved through several algorithms. In this paper the performance of Least Mean Square (LMS), Normalized LMS (NLMS), Variable Step size LMS (VSLMS), Variable Step size NLMS (VSNLMS) and Recursive Least Square (RLS) adaptive filters are compared and their results are discussed.