An audio signal detection system based on laser speckle and multi-channel data fusion is presented. A linear CMOS array is used as the detector, which owns a fast line rate and suitable sensing size. The signals from the pixels are selected and fused to enhance the reconstructed signal. The reconstructed audio signals are evaluated with a segmental SNR (SegSNR) algorithm. The experimental results of three categories of audio sources (single voice audio, conversation and music) show that data fusion can improve the SegSNR scores. Especially, direct phase-error based filtering (pbf) fusion gives a nearly 3.0 dB increase and obtains another 1.0 dB increase with the combination of single channel process. The experimental results show that the fusion algorithms are not sensitive to audio types and the performance of multi-channel data fusion is not weakened with the increase of measuring distance. This feature has potential applications in remote sensing. The intelligibility of the fused audio signals is evaluated with normalized subband envelope correlation (NSEC) algorithm and the evaluation results shows that fusion can also enhance the intelligibility of the recovered signal.