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View Code? Open in Web Editor NEWLEARNING A REPRESENTATION FOR COVER SONG IDENTIFICATION USING CONVOLUTIONAL NEURAL NETWORK. ICASSP2020
License: MIT License
LEARNING A REPRESENTATION FOR COVER SONG IDENTIFICATION USING CONVOLUTIONAL NEURAL NETWORK. ICASSP2020
License: MIT License
作者您好,在test的时候cut_data_front函数中当data.shape[0] < 200的时候需要对数据补零,如果两个不同音频的cqt的长度一个70 一个80的话,对他们都进行补零,那么对特征进行欧氏距离计算,则距离会相对较小,极容易误认为是相似的音频,请问对cqt长度小于200的情况,该如何处理呢?期待您的回复,谢谢~
in CQTNet, there is no Augment.position layer, but when i load the state of the pretrained model, it will occur wrong msg,
Hi there,
Could you please provide the dataset ?
I used your other repository's data directory (https://github.com/yzspku/TPPNet/tree/master/data) but still not all dataset are available for instance you350_list is not there.
Thanks.
this is my cover80 result:
epoch: 0 MAP: 0.7362192759783864 top10: 0.08375 rank1: 9.3625
MAP=0.736 may not equal to MAP=0.840 reference in arcticle
作者您好,能提供一下SHS100K 的CQT 特征嘛。或者怎样去通过YouTube的url去生成SHS100K 的CQT 特征呢
作者您好,在论文中最后的全连接层FC1设置的输出维度为4611。训练集中存在84340首歌曲,由于非连续,存在例如5982_7代表label为5982的第七首翻唱。这样训练会报IndexError: Target 5982 is out of bounds.
代码中FC1全连接层的输出维度是10000。我应该是把训练集中不连续的数据进行处理,保持FC1为4611,还是设置为10000进行训练呢。
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