Update README.md

README.md

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 license: cc-by-nc-4.0
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+# StoryTTS
+
+> [STORYTTS: A HIGHLY EXPRESSIVE TEXT-TO-SPEECH DATASET WITH RICH TEXTUAL EXPRESSIVENESS ANNOTATIONS](https://ieeexplore.ieee.org/document/10446023)
+
+StoryTTS is a highly expressive text-to-speech dataset that contains rich expressiveness both in acoustic and textual perspective, from the recording of a Mandarin storytelling show (评书), which is delivered by a female artist, Lian Liru(连丽如). It contains 61 hours of consecutive and highly prosodic speech equipped with accurate text transcriptions and rich textual expressiveness annotations.
+
+[Demos](https://goarsenal.github.io/StoryTTS/)
+
+[More Info](https://github.com/X-LANCE/StoryTTS)
+
+
+## File Description
+
+* `StoryTTS.zip`: The audio data of StoryTTS.
+* `transcript` : The transcripts of StoryTTS in simplified Chinese with puncuations.
+  
+## Note
+
+  * The dataset is **ONLY** for research purposes.
+  * The ownership of the speech data remains with the original owner. Downloading this dataset defaults to agreeing to sign our [licensing agreement](https://github.com/X-LANCE/StoryTTS/blob/main/storytts_license_agreement.pdf). lt's important to note that these materials may be removed at any time upon request from the original owner.
+
+## Citation
+
+```
+@inproceedings{storytts,
+  author={Sen Liu and Yiwei Guo and Xie Chen and Kai Yu},
+  title={{StoryTTS: A Highly Expressive Text-to-Speech Dataset with Rich Textual Expressiveness Annotations}},
+  year={2024},
+  booktitle={ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
+  pages={11521-11525},
+  doi={10.1109/ICASSP48485.2024.10446023}
+}
+```
+