The double-talk scenario will deteriorate the performance of echo canceller in acoustic echo cancellation， while traditional double-talk detection and other methods of controlling the adaptive step-size cannot effectively deal with it. To solve this problem， a method of adjusting the adaptive step-size according to the spectral signal-to-interference ratio （the ratio of the near-end speech’s power spectrum to the echo’s power spectrum） is proposed. In order to reduce computational complexity and processing delay， the partitioned frequency block least mean square （PFBLMS） algorithm is used as the adaptive filtering algorithm. So the adaptive step-size is adjusted in the frequency domain. First， the relationship between the spectral signal-to-interference ratio and the coherence function is established. Second， the step-size is obtained through the coherence function. Third， the adaptive step-size of each frequency point is adjusted in real time according to the calculated value. In addition， the dual filter and the sparse control algorithms are combined to further improve robustness and convergence performance of the system. The computer simulation shows that the system can not only guarantee good echo suppression ability in the double-talk scenario， but also track the changes of the echo channel in time. Compared with the double-talk detection method based on the normalized cross-correlation function and the echo cancellation algorithm in the open source project Speex， the proposed system achieves better echo return loss enhancement （ERLE） and perceptual evaluation of speech quality （PESQ）.