Update README.md

README.md

@@ -12,7 +12,7 @@ For the task named Multimodal Emotion-Cause Pair Extraction in Conversation, we
 
 For more details, please refer to our GitHub: 
 
-- [Multimodal Emotion-Cause Pair Extraction in Conversations](https://github.com/NUSTM/MECPE)
+- [Multimodal Emotion-Cause Pair Extraction in Conversations](https://github.com/NUSTM/MECPE/tree/main/data)
 - [SemEval-2024 Task 3](https://github.com/NUSTM/SemEval-2024_ECAC)
 
 ## Dataset Statistics
@@ -24,6 +24,23 @@ For more details, please refer to our GitHub:
 | Emotion (utterances)            | 5,577 | 668   | 1,445 | 7,690  |
 | Emotion-cause (utterance) pairs | 7,055 | 866   | 1,873 | 9,794  |
 
+## About Multimodal Data   
+
+⚠️ Due to potential copyright issues with the TV show "Friends", we do not provide pre-segmented video clips. 
+
+If you need to utilize multimodal data, you may consider the following options:
+
+1. Use the acoustic and visual features we provide:
+    - [`audio_embedding_6373.npy`](https://drive.google.com/file/d/1EhU2jFSr_Vi67Wdu1ARJozrTJtgiQrQI/view?usp=share_link): the embedding table composed of the 6373-dimensional acoustic features of each utterances extracted with openSMILE
+    - [`video_embedding_4096.npy`](https://drive.google.com/file/d/1NGSsiQYDTqgen_g9qndSuha29JA60x14/view?usp=share_link): the embedding table composed of the 4096-dimensional visual features of each utterances extracted with 3D-CNN
+
+2. Since ECF is constructed based on the MELD dataset, you can download the raw video clips from [MELD](https://github.com/declare-lab/MELD). 
+Most utterances in ECF align with MELD. However, **we have made certain modifications to MELD's raw data while constructing ECF, including but not limited to editing utterance text, adjusting timestamps, and adding or removing utterances**. Therefore, some timestamps provided in ECF have been corrected, and there are also new utterances that cannot be found in MELD. Given this, we recommend option (3) if feasible.
+
+3. Download the raw videos of _Friends_ from the website, and use the FFmpeg toolkit to extract audio-visual clips of each utterance based on the timestamps we provide.
+
+   
+
 ## Citation
 
 If you find ECF useful for your research, please cite our paper using the following BibTeX entries: