syncs

README.md

@@ -32,7 +32,7 @@ We have constructed the [default subset](#default-subset) of the current integra
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-Due to the large number of categories in this dataset, we are unable to provide the audio duration per category and the proportion of audio clips by category, as we have done for other datasets. Instead, we provide a chart showing the distribution of the number of audio clips across different durations, as shown in **Fig. 1**. Along with a chart, displayed in **Fig. 2**, showing the instrument categories distribution across various durations. From **Fig. 1**, 4,277 clips (86%) are concentrated in the 0-45 second range, with a steep drop in the number of samples in longer durations. For the longest duration interval (450-495 seconds), the corresponding category is Konghou only. In **Fig. 2**, the audio duration of 211 instrument categories is less than 1755 seconds. While 8 classes have audio duration longer than this. The single instrument that possesses the longest audio duration is Zhongruan. This indicates that there is only a slight class imbalance problem for this dataset.
+Due to the large number of categories in this dataset, we are unable to provide the audio duration per category and the proportion of audio clips by category, as we have done for the other datasets. Instead, we provide a chart showing the distribution of the number of audio clips across different durations, as shown in **Fig. 1**. A second graph, shown in **Fig. 2**, shows the distribution of instrument categories over various durations. From **Fig. 1**, 3611 clips (73%) are concentrated in the range 0-27.5 s, with a steep drop in the number of samples in longer durations. In **Fig. 2**, about half of the instruments, totaling 117, have a duration of less than 437 seconds, while 102 instruments have a duration greater than this number. After the total duration exceeds 881 seconds, the number of instruments drops sharply. This indicates that the dataset has a certain degree of class imbalance.
 
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