中文摘要：

提出了基于Gammachirp耳蜗能量谱的音频时频域特征表示方法,并在此基础上进一步构造了一种音频指纹算法。首先利用非负矩阵分解（Non-negative Matrix Factorization,NMF）提取Gammachirp耳蜗能量谱的局部特征,然后对该局部特征进行差分和量化,以提高算法的鲁棒性,并降低检索的计算复杂度。实验结果表明：在经受音频编辑软件多种攻击和实际环境中录音检索时,本文算法都具有很好的鲁棒性和识别率。

英文摘要：

By means of Gammachirp-cochleagram, this paper presents a novel time-frequency representation algorithm for audio features. The local feature of the Gammachirp-cochleagram is firstly extracted by non-negative matrix factorization （NMF）. And then, both the difference and the quantization are applied on the extracted features to further enhance its robustness and reduce its computational complexity. Experimental results illustrate that the proposed algorithm achieves superior performance in robustness and identification rate under the attack of audio editing software and the searching of record.