Abstract：Key audio detection, an important form of audio retrieval, uses a query audio sample to search in an audio database but such searches are not very efficient or robust. This paper optimizes the pre-processing, fingerprint extraction and retrieval of the audio retrieval. The pre-processing uses endpoint detection based on the sub-band energy ratio with a modified window function and measurements of the sub-band divisions. The fingerprint extraction uses seed fragments and spectral sub-band centroids. The retrieval part uses a threshold for the hit counts to improve the efficiency. This system improves the precision and reduces the recall rate with good noise suppression. The retrieval efficiency and performance are effectively improved.
孙甲松, 张菁芸, 杨毅. 基于子带频谱质心特征的高效音频指纹检索[J]. 清华大学学报（自然科学版）, 2017, 57(4): 382-387.
SUN Jiasong, ZHANG Jingyun, YANG Yi. Effective audio fingerprint retrieval based on the spectral sub-band centroid feature. Journal of Tsinghua University(Science and Technology), 2017, 57(4): 382-387.
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2017, Vol. 57 
