Automatic subgrouping of multitrack audio
Automatic subgrouping of multitrack audio
复制标题
多轨音频自动分组
DOI：
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发表时间：
2015
期刊：
影响因子：
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通讯作者：
J. Reiss
中科院分区：
文献类型：
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作者：
D. Ronan;H. Gunes;D. Moffat;J. Reiss
分组是一种混合技术，其中多轨道中的音频轨道的子集的输出被求和到单个音频总线。这样做是为了让混音工程师可以将信号处理应用于整个子组，加快混音工作流程，并一次处理多个音轨。在这项工作中，我们调查的音频功能，从一组159可用于自动分组多轨音频。我们从原始的159个音频特征中确定一个音频特征子集，用于自动分组，通过使用随机森林分类器对54个单独的多轨数据集进行特征选择。我们表明，通过使用凝聚聚类5测试多轨道，整个音频功能不正确的集群的35.08%的音轨，而音频功能的子集不正确的集群只有7.89%的音轨。此外，我们还表明，使用整个音频功能集，创建了十个不正确的子组。然而，当使用音频特征的子集时，仅创建五个不正确的子组。这表明我们减少的音频特征集为自动创建子组提供了分类准确性的显着提高。
Subgrouping is a mixing technique where the outputs of a subset of audio tracks in a multitrack are summed to a single audio bus. This is done so that the mix engineer can apply signal processing to an entire subgroup, speed up the mix work flow and manipulate a number of audio tracks at once. In this work, we investigate which audio features from a set of 159 can be used to automatically subgroup multitrack audio. We determine a subset of audio features from the original 159 audio features to use for automatic subgrouping, by performing feature selection using a Random Forest classifier on a dataset of 54 individual multitracks. We show that by using agglomerative clustering on 5 test multitracks, the entire set of audio features incorrectly clusters 35.08% of the audio tracks, while the subset of audio features incorrectly clusters only 7.89% of the audio tracks. Furthermore, we also show that using the entire set of audio features, ten incorrect subgroups are created. However, when using the subset of audio features, only five incorrect subgroups are created. This indicates that our reduced set of audio features provides a significant increase in classification accuracy for the creation of subgroups automatically.