计算机科学 ›› 2022, Vol. 49 ›› Issue (3): 179-184.doi: 10.11896/jsjkx.201200081
黎思泉, 万永菁, 蒋翠玲
LI Si-quan, WAN Yong-jing, JIANG Cui-ling
摘要： 多基频估计被广泛应用于音乐结构分析、乐音辅助教育、信息检索等各个领域。为了满足准确识别乐曲中随机和弦的需求,提出了基于生成对抗网络去影像的多基频估计算法。首先将完整音频切分成音符段,提出了一种谐音指纹图提取音符段频谱特征;然后通过卷积神经网络识别谐音指纹图当前的主导基频,将已识别出的主导基频作为干扰下一个基频识别的影像,并通过生成对抗网络去除干扰影像,对已去除干扰影像后的谐音指纹图进行新一轮的多基频估计;最后通过逐级迭代去影像操作实现完整和弦的多基频估计。对随机二音和弦及随机三音和弦组成的钢琴音频数据库进行实验,结果表明,所提算法与经典频谱迭代删除算法和大型词袋和弦识别算法相比,能够适应随机和弦的识别,在不同的音域范围内鲁棒性高,整体正确率有明显提升。
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