Nonlinear Acoustic Echo Cancellation for Mobile Phones: A Practical Approach

Abstract: Acoustic echo cancelation (AEC) composes a fundamental property of speech processing to enable a pleasant telecommunication conversation. Without this property of the telephone the communicator would hear an annoying echo of his own voice along with the speech from the other communicator. This would make a conversation through any telecommunication device an unpleasant experience. AEC has been subject of interest since 1950s in the telecom industry and very efficient solutions were devised to cancel linear echo. With the advent of low cost hands free communication devices the issue of non linear echo became prominent because these devices use cheap loudspeakers that produce artifacts in addition to the desired sound which will cause non linear echo that cannot be cancelled by linear echo cancellers. In this thesis a Harmonic Distortion Residual Echo Cancelation algorithm has been chosen for further investigations (HDRES). HDRES has many of those features that are desirable for an algorithm which is dealing with nonlinear acoustic echo cancelation, such as low computational complexity and fast convergence. The algorithm was first implemented in Matlab where it was tested and modified. The final result of the modified algorithm was then implemented in C and integrated with a complete AEC system. Before the implementation a number of measurements were done to distinguish the nonlinearities that were cause by the mobile phone loudspeaker. The measurements were performed on three different mobile pones which were documented to have problems with nonlinear acoustic echo. The result of this thesis has shown that it might be possible to use an adaptive filter, which has both low complexity and fast convergence, in an operating AEC system. However, the request for such a system to work would be that a doubletalk detector is implemented along with the adaptive algorithm. That way the doubletalk situation could be found and the adaptation of the algorithm could be stopped. Thus, the major part of the speech would be saved.