In this Letter, a residual acoustic echo suppression method is proposed to enhance the speech quality of hands-free communication in an automobile environment. The echo signal is normally a human voice with harmonic characteristics in a hands-free communication environment. The proposed algorithm estimates the residual echo signal by emphasizing its harmonic components. The estimated residual echo is used to obtain the signal-to-interference ratio (SIR) information at the acoustic echo canceller output. Then, the SIR based Wiener post-filter is constructed to reduce both the residual echo and noise. The experimental results confirm that the proposed algorithm is superior to the conventional residual echo suppression algorithm in terms of the echo return loss enhancement (ERLE) and the segmental signal-to-noise ratio (SEGSNR).

A simple and novel residual acoustic echo cancellation method that employs binary masking is proposed to enhance the speech quality of hands-free communication in an automobile environment. In general, the W-disjoint orthogonality assumption is used for blind source separation using multi-microphones. However, in this Letter, it is utilized to mask the residual echo component in the time-frequency domain using a single microphone. The experimental results confirm the effectiveness of the proposed method in terms of the echo return loss enhancement and speech enhancement.

A residual acoustic echo cancellation method that employs the masking property is proposed to enhance the speech quality of hands-free communication devices in an automobile environment. The conventional masking property is employed for speech enhancement using the masking threshold of the desired clean speech signal. In this Letter, either the near-end speech or residual noise is selected as the desired signal according to the double-talk detector. Then, the residual echo signal is masked by the desired signal (masker). Experiments confirm the effectiveness of the proposed method by deriving the echo return loss enhancement and by examining speech waveforms and spectrograms.