upd md

README.md

@@ -21,9 +21,6 @@ The original dataset, sourced from the [Acapella Evaluation Dataset](https://ccm
 
 Due to the original dataset comprising separate files for audio recordings and evaluation sheets, which hindered efficient data retrieval, we combined the original vocal recordings with their corresponding evaluation sheets to construct the [default subset](#usage) of the current integrated version of the dataset. The data structure can be viewed in the [viewer](https://www.modelscope.cn/datasets/ccmusic-database/acapella/dataPeview). The current dataset is already endorsed by published articles, hence there is no need to construct the eval subset.
 
-## Viewer
-<https://www.modelscope.cn/datasets/ccmusic-database/acapella/dataPeview>
-
 ## Dataset Structure
 <style>
   .datastructure td {
@@ -47,12 +44,6 @@ Due to the original dataset comprising separate files for audio recordings and e
         <td>int</td>
         <td>float(0-10)</td>
     </tr>
-    <tr>
-        <td>...</td>
-        <td>...</td>
-        <td>...</td>
-        <td>...</td>
-    </tr>
 </table>
 
 ### Data Instances
@@ -65,12 +56,6 @@ song, singer id, pitch, rhythm, vocal range, timbre, pronunciation, vibrato, dyn
 song1-6
 
 ## Dataset Description
-- **Homepage:** <https://ccmusic-database.github.io>
-- **Repository:** <https://huggingface.co/datasets/ccmusic-database/acapella_evaluation>
-- **Paper:** <https://doi.org/10.5281/zenodo.5676893>
-- **Leaderboard:** <https://www.modelscope.cn/datasets/ccmusic-database/acapella>
-- **Point of Contact:** <https://www.mdpi.com/2076-3417/12/19/9931>
-
 ### Dataset Summary
 Due to the original dataset comprising separate files for audio recordings and evaluation sheets, which hindered efficient data retrieval, we have consolidated the raw vocal recordings with their corresponding assessments. The dataset is divided into six segments, each representing a different song, resulting in a total of six divisions. Each segment contains 22 entries, with each entry detailing the vocal recording of an individual singer sampled at 22,050 Hz, the singer's ID, and evaluations across the nine dimensions previously mentioned. Consequently, each entry encompasses 11 columns of data. This dataset is well-suited for tasks such as vocal analysis and regression-based singing voice rating. For instance, as previously stated, the final column of each entry denotes the overall performance score, allowing the audio to be utilized as data and this score to serve as the label for regression analysis.
 
@@ -136,14 +121,12 @@ Zijin Li
 
 ### Citation Information
 ```bibtex
-@dataset{zhaorui_liu_2021_5676893,
-  author       = {Monan Zhou, Shenyang Xu, Zhaorui Liu, Zhaowen Wang, Feng Yu, Wei Li and Baoqiang Han},
-  title        = {CCMusic: an Open and Diverse Database for Chinese and General Music Information Retrieval Research},
-  month        = {mar},
-  year         = {2024},
-  publisher    = {HuggingFace},
-  version      = {1.2},
-  url          = {https://huggingface.co/ccmusic-database}
+@article{Li2022SingingVoiceTE,
+  title={Singing-Voice Timbre Evaluations Based on Transfer Learning},
+  author={Rongfeng Li and Mingtong Zhang},
+  journal={Applied Sciences},
+  year={2022},
+  url={https://api.semanticscholar.org/CorpusID:252766951}
 }
 ```
 ### Contributions