upd md

README.md

@@ -87,7 +87,7 @@ In the original dataset, the labels were represented by folder names, which prov
 
 Based on the aforementioned original dataset, we conducted data processing to construct the [default subset](#default-subset) of the current integrated version of the dataset. Due to the pre-existing split in the original dataset, wherein the data has been partitioned approximately in a 4:1 ratio for training and testing sets, we uphold the original data division approach for the default subset. The data structure of the default subset can be viewed in the [viewer](https://huggingface.co/datasets/ccmusic-database/GZ_IsoTech/viewer). In addition, we have retained the [eval subset](#eval-subset) used in the experiment for easy replication.
 
-## Default Subset Structure
+## Data Structure
 <https://huggingface.co/datasets/ccmusic-database/GZ_IsoTech/viewer>
 
 ### Data Instances
@@ -105,8 +105,7 @@ A dataset for Guzheng playing technique classification
 | :---------------------------------------------------------------------------------------------------: | :-----------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------------: |
 |                                              **Fig. 1**                                               |                                            **Fig. 2**                                             |                                              **Fig. 3**                                               |
 
-Firstly, **Fig. 1** illustrates the number and proportion of audio clips in each category. The category with the largest proportion is Upward Portamento, accounting for 19.0% with 536 clips. The smallest category is Tremolo, accounting for 8.1% with 228 clips. The difference in proportion between the largest and smallest categories is 10.9%. Next, **Fig. 2** displays the total audio duration for each category. The category with the longest total duration is Upward Portamento, with 14.11 minutes, consistent with the results shown in the pie chart. However, the category with the shortest total duration is Plucks, with a total of 5.06 minutes, which differs from the ranking in the pie chart. Overall, this dataset is comparatively balanced within the database. Finally, **Fig. 3** presents the number of audio clips distributed across different duration intervals. 
-Most of the audio clips are concentrated in the 0-3 second range. Among them, 1,742 audio clips are concentrated in the 0-1.5 second range, while 1,033 clips are concentrated in the 1.5-3 second range. Only 49 clips exceed 3 seconds in length.
+Firstly, **Fig. 1** illustrates the number and proportion of audio clips in each category. The category with the largest proportion is Upward Portamento, accounting for 19.0% with 536 clips. The smallest category is Tremolo, accounting for 8.1% with 228 clips. The difference in proportion between the largest and smallest categories is 10.9%. Next, **Fig. 2** displays the total audio duration for each category. The category with the longest total duration is Upward Portamento, with 14.11 minutes, consistent with the results shown in the pie chart. However, the category with the shortest total duration is Plucks, with a total of 5.06 minutes, which differs from the ranking in the pie chart. Overall, this dataset is comparatively balanced within the database. Finally, **Fig. 3** presents the number of audio clips distributed across different duration intervals. Most of the audio clips are concentrated in the 0-3 second range. Among them, 1,742 audio clips are concentrated in the 0-1.5 second range, while 1,033 clips are concentrated in the 1.5-3 second range. Only 49 clips exceed 3 seconds in length.
 
 |  Statistical items  |        Values        |
 | :-----------------: | :------------------: |
@@ -175,7 +174,7 @@ Dichucheng Li
   author    = {Dichucheng Li and Yulun Wu and Qinyu Li and Jiahao Zhao and Yi Yu and Fan Xia and Wei Li},
   title     = {Playing Technique Detection by Fusing Note Onset Information in Guzheng Performance},
   booktitle = {Proceedings of the 23rd International Society for Music Information Retrieval Conference, {ISMIR} 2022, Bengaluru, India, December 4-8, 2022},
-  pages     = {314--320},
+  pages     = {314-320},
   year      = {2022}
 }
 ```