Update README.md

README.md

@@ -1,3 +1,44 @@
 ---
 license: apache-2.0
+language:
+- en
+tags:
+- MuseCoco
+- Text2Music
 ---
+
+<p align="center" width="100%">
+<a href="" target="_blank"><img src="https://ai-muzic.github.io/images/musecoco/framework.png" alt="Text2Attribute" style="width: 60%; min-width: 60px; display: block; margin: auto;"></a>
+</p>
+
+# Text-to-Attribute Understanding
+This is the text-to-attribute model to extract musical attributes from text, introduced in the paper [*MuseCoco: Generating Symbolic Music from Text*](https://arxiv.org/abs/2306.00110) and [first released in this repository](https://github.com/microsoft/muzic/tree/main/musecoco).
+It is based on BERT-large and has multiple classification heads for diverse musical attributes.
+
+There is the mapping between keywords used in the model and musical attributes:
+```json
+{
+    "I1s2": "Instrument",
+    "R1": "Rhythm Danceability",
+    "R3": "Rhythm Intensity",
+    "S2s1": "Artist",
+    "S4": "Genre",
+    "B1s1": "Bar",
+    "TS1s1": "Time Signature",
+    "K1": "Key",
+    "T1s1": "Tempo",
+    "P4": "Pitch Range",
+    "EM1": "Emotion",
+    "TM1": "Time"
+}
+```
+
+# BibTeX entry and citation info
+```bibtex
+@article{musecoco2023,
+  title={MuseCoco: Generating Symbolic Music from Text},
+  author={Peiling Lu, Xin Xu, Chenfei Kang, Botao Yu, Chengyi Xing, Xu Tan, Jiang Bian},
+  journal={arXiv preprint arXiv:2306.00110},
+  year={2023}
+}
+```