Merge branch 'main' of https://huggingface.co/datasets/IVLLab/MultiDialog into main

README.md

@@ -25,10 +25,21 @@ size_categories:
 - **Point of Contact:** [[email protected]](mailto:[email protected])
 
 ## Dataset Description
-This dataset includes manually annotated metadata linking audio files to transcriptions, emotions, and other attributes. 
+This dataset includes manually annotated metadata linking audio files to transcriptions, emotions, and other attributes. For access to video files of MultiDialog, download them [here](https://drive.google.com/drive/folders/1RPMwVHU34yX0R_HbxAWmxF2EHy961HA3?usp=sharing).
+
+### Dataset Statistics
+|                       | train   | valid_freq | valid_rare | test_freq | test_rare | Total    |
+|-----------------------|---------|---------|---------|---------|---------|----------|
+| \# dialogues          | 7,011   | 448     | 443     | 450     | 381     | 8,733    |
+| \# utterance          | 151,645 | 8,516   | 9,556   | 9,811   | 8,331   | 187,859  |
+| avg \# utterance/dialogue  | 21.63   | 19.01   | 21.57   | 21.80   | 21.87   | 21.51    |
+| avg length/utterance (s)  | 6.50    | 6.23    | 6.40    | 6.99    | 6.49    | 6.51     |
+| avg length/dialogue (min)  | 2.34    | 1.97    | 2.28    | 2.54    | 2.36    | 2.33     |
+| total length (hr)  | 273.93  | 14.74   | 17.00   | 19.04   | 15.01   | 339.71   |
+
 
 ### Example Usage
-There are 'train', 'test_freq', 'test_rare', 'valid_freq', and 'valid_rare' splits. Below is the example usage. 
+There are 'train', 'test_freq', 'test_rare', 'valid_freq', and 'valid_rare' splits. Below is an example usage. 
 ```python
 from datasets import load_dataset
 
@@ -43,34 +54,41 @@ transcription = MultiD["valid_freq"][0]["value"]  # first transcription
 ```
 
 ### Supported Tasks
-- `multimodal dialogue generation` 
+- `multimodal dialogue generation` : The dataset can be used to train an end-to-end multimodal 
 - `automatic-speech-recognition`: The dataset can be used to train a model for Automatic Speech Recognition (ASR). 
 - `text-to-speech`: The dataset can also be used to train a model for Text-To-Speech (TTS).
 
 ### Languages
 Multidialog contains audio and transcription data in English.
 
+### Gold Emotion Dialogue Subset
+We provide a gold emotion dialogue subset in the MultiDialog dataset, a more reliable resource for studying emotional dynamics in conversations. 
+We classify dialogues from actors that exhibit emotion accuracy above 40% as gold emotion dialogue. Please use dialogues from actors with the following ids: a, b, c, e, f, g, i, j, and k.
+
+
 ## Dataset Structure
 ### Data Instances
 ```python
 {
+    'file_name': 't_ffa55df6-114d-4b36-87a1-7af6b8b63d9b/t_ffa55df6-114d-4b36-87a1-7af6b8b63d9b_0k.wav'
     'conv_id': 't_ffa55df6-114d-4b36-87a1-7af6b8b63d9b', 
     'utterance_id': 0,
     'from': 'gpt', 
     'audio': 
         {
-            # in streaming mode 'path' will be 'xs_chunks_0000/YOU0000000315_S0000660.wav'
-            'path': '/home/user/.cache/huggingface/datasets/downloads/extracted/9d48cf31/xs_chunks_0000/YOU0000000315_S0000660.wav', 
+            # in streaming mode 'path' will be 't_152ee99a-fec0-4d37-87a8-b1510a9dc7e5/t_152ee99a-fec0-4d37-87a8-b1510a9dc7e5_0i.wav'
+            'path': '/home/user/.cache/huggingface/datasets/downloads/extracted/cache_id/t_152ee99a-fec0-4d37-87a8-b1510a9dc7e5/t_152ee99a-fec0-4d37-87a8-b1510a9dc7e5_0i.wav, 
             'array': array([0.0005188 , 0.00085449, 0.00012207, ..., 0.00125122, 0.00076294, 0.00036621], dtype=float32), 
             'sampling_rate': 16000
         },
     'value': 'Are you a football fan?', 
     'emotion': 'Neutral', 
-    'original_full_path': 'audio/youtube/P0004/YOU0000000315.opus'
+    'original_full_path': 'valid_freq/t_ffa55df6-114d-4b36-87a1-7af6b8b63d9b/t_ffa55df6-114d-4b36-87a1-7af6b8b63d9b_0k.wav'
 }
 ```
 
 ### Data Fields
+* file_name (string) - relative file path to the audio sample in the specific split directory.
 * conv_id (string) - unique identifier for each conversation.
 * utterance_id (float) -  uterrance index.
 * from (string) - who the message is from (human, gpt).