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Table 7: Top10-ranked bigram word features for each mood category. lable 8: Top10-ranked trigram word features for each mood category.

Table 7 Top10-ranked bigram word features for each mood category. lable 8: Top10-ranked trigram word features for each mood category.

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Figure 1: Music mood classification process steps.
Figure 1: Music mood classification process steps.
Table 1: Four emotion cluster of proposed mood taxonomy. Each one of the selected Turkish songs is tagged by at least 3 different volunteered human taggers, where each one comes from the same socio-economic background and education. Each tagger was a PhD student in department of Management Information Systems. They worked independently and assigned a tag to one of the 4 mood categories. At the end, more than 400 songs are tagged by the human annotators, and among the ones where there is an agreement among at least two of the three annotators, 300 of them are selected in such a way to obtain the class balance between the mood categories as given in Table 2.
Table 1: Four emotion cluster of proposed mood taxonomy. Each one of the selected Turkish songs is tagged by at least 3 different volunteered human taggers, where each one comes from the same socio-economic background and education. Each tagger was a PhD student in department of Management Information Systems. They worked independently and assigned a tag to one of the 4 mood categories. At the end, more than 400 songs are tagged by the human annotators, and among the ones where there is an agreement among at least two of the three annotators, 300 of them are selected in such a way to obtain the class balance between the mood categories as given in Table 2.
Table 2: Summary of ground truth data collection. 3.3 Preprocessing of the Turkish song lyrics and feature extraction
Table 2: Summary of ground truth data collection. 3.3 Preprocessing of the Turkish song lyrics and feature extraction
Table 3: Best accuracy scores obtained for each stemming method. Table 4: Combination of methods given for the Top 10 accuracy scores.
Table 3: Best accuracy scores obtained for each stemming method. Table 4: Combination of methods given for the Top 10 accuracy scores.
Table 5: Accuracy scores obtained for each mood category where Zemberek Long stemming method is utilized.
Table 5: Accuracy scores obtained for each mood category where Zemberek Long stemming method is utilized.
Table 6: Top10-ranked unigram word features for each mood category.
Table 6: Top10-ranked unigram word features for each mood category.
Related topics:
Music Emotion Classification
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