Update README.md

README.md

@@ -32,6 +32,7 @@ Dataset of [GTSinger (NeurIPS 2024 Spotlight)](https://arxiv.org/abs/2409.13832)
 [![arXiv](https://img.shields.io/badge/arXiv-Paper-<COLOR>.svg)](https://arxiv.org/abs/2409.13832) 
 [![GitHub](https://img.shields.io/badge/GitHub-Repo-black.svg)](https://github.com/AaronZ345/GTSinger)
 [![weixin](https://img.shields.io/badge/-WeChat@机器之心-000000?logo=wechat&logoColor=07C160)](https://mp.weixin.qq.com/s/B1Iqr-24l57f0MslzYEslA)
+[![weixin](https://img.shields.io/badge/-WeChat@PaperWeekly-000000?logo=wechat&logoColor=07C160)](https://mp.weixin.qq.com/s/6RLdUzJM5PItklKUTTNz2w)
 [![zhihu](https://img.shields.io/badge/-知乎-000000?logo=zhihu&logoColor=0084FF)](https://zhuanlan.zhihu.com/p/993933492)
 [![Google Drive](https://img.shields.io/badge/Google%20Drive-Link-blue?logo=googledrive&logoColor=white)](https://drive.google.com/drive/folders/1xcdvCxNAEEfJElt7sEP-xT8dMKxn1_Lz?usp=drive_link)
 
@@ -47,9 +48,114 @@ Moreover, you can visit our [Demo Page](https://aaronz345.github.io/GTSingerDemo
 
 **Please note that, if you are using GTSinger, it means that you have accepted the terms of [license](./dataset_license.md).**
 
+## Key Features
+
+- **80.59 hours of singing voices** in GTSinger are recorded in professional studios by skilled singers, ensuring **high quality and clarity**, forming the largest recorded singing dataset.
+- Contributed by **20 singers** across **nine widely spoken languages** (Chinese, English, Japanese, Korean, Russian, Spanish, French, German, and Italian) and all four vocal ranges, GTSinger enables zero-shot SVS and style transfer models to learn diverse timbres and styles.
+- GTSinger provides **controlled comparison** and **phoneme-level annotations** of **six singing techniques** (mixed voice, falsetto, breathy, pharyngeal, vibrato, and glissando) for songs, thereby facilitating singing technique modeling, recognition, and control.
+- Unlike fine-grained music scores, GTSinger features **realistic music scores** with regular note duration, assisting singing models in learning and adapting to real-world musical composition.
+- The dataset includes **manual phoneme-to-audio alignments, global style labels** (singing method, emotion, range, and pace), and **16.16 hours of paired speech**, ensuring comprehensive annotations and broad task suitability.
+
 ## Updates
 
 - 2024.10: We refine the paired speech data of each language!
 - 2024.10: We released the processed data of Chinese, English, Spanish, German, Russian!
 - 2024.09: We released the full dataset of GTSinger!
 - 2024.09: GTSinger is accepted by NeurIPS 2024 (Spotlight)!
+
+## Dataset
+
+### Where to download
+
+Through this repo you can access our **full dataset** (audio along with TextGrid, json, musicxml) and **processed data** (metadata.json, phone_set.json, spker_set.json) on Hugging Face **for free**! Hope our data is helpful for your research.
+
+Besides, we also provide our dataset on [![Google Drive](https://img.shields.io/badge/Google%20Drive-Link-blue?logo=googledrive&logoColor=white)](https://drive.google.com/drive/folders/1xcdvCxNAEEfJElt7sEP-xT8dMKxn1_Lz?usp=drive_link).
+
+### Data Architecture
+
+Our dataset is organized hierarchically. 
+
+It presents nine top-level folders, each corresponding to a distinct language. 
+
+Within each language folder, there are five sub-folders, each representing a specific singing technique.
+
+These technique folders contain numerous song entries, with each song further divided into several controlled comparison groups: a control group (natural singing without the specific technique), and a technique group (densely employing the specific technique).
+
+Our singing voices and speech are recorded at a 48kHz sampling rate with 24-bit resolution in WAV format. 
+
+Alignments and annotations are provided in TextGrid files, including word boundaries, phoneme boundaries, phoneme-level annotations for six techniques, and global style labels (singing method, emotion, pace, and range). 
+
+We also provide realistic music scores in musicxml format.
+
+Notably, we provide an additional JSON file for each singing voice, facilitating data parsing and processing for singing models.
+
+Here is the data structure of our dataset:
+
+```
+.
+├── Chinese
+│   ├── ZH-Alto-1
+│   └── ZH-Tenor-1
+├── English
+│   ├── EN-Alto-1
+│   │   ├── Breathy
+│   │   ├── Glissando
+│   │   │   └── my love
+│   │   │       ├── Control_Group
+│   │   │       ├── Glissando_Group
+│   │   │       └── Paired_Speech_Group
+│   │   ├── Mixed_Voice_and_Falsetto
+│   │   ├── Pharyngeal
+│   │   └── Vibrato
+│   ├── EN-Alto-2
+│   │   ├── Breathy
+│   │   ├── Glissando
+│   │   ├── Mixed_Voice_and_Falsetto
+│   │   ├── Pharyngeal
+│   │   └── Vibrato
+│   └── EN-Tenor-1
+│       ├── Breathy
+│       ├── Glissando
+│       ├── Mixed_Voice_and_Falsetto
+│       ├── Pharyngeal
+│       └── Vibrato
+├── French
+│   ├── FR-Soprano-1
+│   └── FR-Tenor-1
+├── German
+│   ├── DE-Soprano-1
+│   └── DE-Tenor-1
+├── Italian
+│   ├── IT-Bass-1
+│   ├── IT-Bass-2
+│   └── IT-Soprano-1
+├── Japanese
+│   ├── JA-Soprano-1
+│   └── JA-Tenor-1
+├── Korean
+│   ├── KO-Soprano-1
+│   ├── KO-Soprano-2
+│   └── KO-Tenor-1
+├── Russian
+│   └── RU-Alto-1
+└── Spanish
+    ├── ES-Bass-1
+    └── ES-Soprano-1
+```
+
+## Citations ##
+
+If you find this code useful in your research, please cite our work:
+```bib
+@article{zhang2024gtsinger,
+  title={Gtsinger: A global multi-technique singing corpus with realistic music scores for all singing tasks},
+  author={Zhang, Yu and Pan, Changhao and Guo, Wenxiang and Li, Ruiqi and Zhu, Zhiyuan and Wang, Jialei and Xu, Wenhao and Lu, Jingyu and Hong, Zhiqing and Wang, Chuxin and others},
+  journal={arXiv preprint arXiv:2409.13832},
+  year={2024}
+}
+```
+
+## Disclaimer ##
+
+Any organization or individual is prohibited from using any technology mentioned in this paper to generate someone's singing without his/her consent, including but not limited to government leaders, political figures, and celebrities. If you do not comply with this item, you could be in violation of copyright laws.
+