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

README.md

@@ -16,16 +16,74 @@ size_categories:
 #         path: test_freq/*, metadata.jsonl
 ---
 
+## Dataset Description
+
+- **Homepage:** https://multidialog.github.io
+- **Repository:** https://github.com/MultiDialog/MultiDialog
+- **Paper:** https://arxiv.org/abs/2106.06909
+- **Point of Contact:** [jinny960812@kaist.ac.kr](mailto:jinny960812@kaist.ac.kr)
+- **Point of Contact:** [chaewonkim@kaist.ac.kr](mailto:chaewonkim@kaist.ac.kr)
+
+## Dataset Description
+This dataset includes manually annotated metadata linking audio files to transcriptions, emotions, and other attributes. 
+
+### Example Usage
+There are 'train', 'test_freq', 'test_rare', 'valid_freq', and 'valid_rare' splits. Below is the example usage. 
+```python
+from datasets import load_dataset
+
+MultiD = load_dataset("IVLLab/MultiDialog", "valid_freq", use_auth_token=True)
+
+# see structure
+print(MultiD)
+
+# load audio sample on the fly
+audio_input = MultiD["valid_freq"][0]["audio"]  # first decoded audio sample
+transcription = MultiD["valid_freq"][0]["value"]  # first transcription
+```
+
+### Supported Tasks
+- `multimodal dialogue generation` 
+- `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.
+
+## Dataset Structure
+### Data Instances
+```python
+{
+    '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', 
+            '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'
+}
+```
+
+### Data Fields
+* conv_id (string) - unique identifier for each conversation.
+* utterance_id (float) -  uterrance index.
+* from (string) - who the message is from (human, gpt).
+* audio (Audio feature) - a dictionary containing the path to the audio, the decoded audio array, and the sampling rate.
+In non-streaming mode (default), the path point to the locally extracted audio. In streaming mode, the path is the relative path of an audio.
+segment inside its archive (as files are not downloaded and extracted locally).
+* value (string) - transcription of the utterance.
+* emotion (string) - the emotion of the utterance.
+* original_full_path (string) - the relative path to the original full audio sample in the original data directory.
+
+Emotion is assigned from the following labels: 
+"Neutral", "Happy", "Fear", "Angry", "Disgusting", "Surprising", "Sad"
 
-# Dataset Description
-This dataset includes manually annotated metadata linking audio files to transcriptions, emotions, and other attributes. The `test_freq.parquet` file contains these links and metadata.
 
-## Data Fields
-- `id`: unique identifier for each conversation.
-- 'utterance' : uterrance index. 
-- `from`: who the message is from (human, gpt)
-- `value`: the text of the utterance.
-- `emotion`: the emotion of the utterance.
-- `audpath`: path to the associated audio file.