Update README.md

README.md

@@ -24,25 +24,23 @@ size_categories:
 - **Point of Contact:** [[email protected]](mailto:[email protected]), [[email protected]](mailto:[email protected])
 
 ## 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.
+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
 
-gs = load_dataset("speechcolab/gigaspeech", "valid_freq", use_auth_token=True)
+MultiD = load_dataset("IVLLab/MultiDialog", "valid_freq", use_auth_token=True)
 
 # see structure
-print(gs)
+print(MultiD)
 
 # load audio sample on the fly
-audio_input = gs["valid_freq"][0]["audio"]  # first decoded audio sample
-transcription = gs["valid_freq"][0]["text"]  # first transcription
+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). 
@@ -52,9 +50,7 @@ transcription = gs["valid_freq"][0]["text"]  # first transcription
 Multidialog contains audio and transcription data in English.
 
 ## Dataset Structure
-
 ### Data Instances
-
 ```python
 {
     'conv_id': 't_ffa55df6-114d-4b36-87a1-7af6b8b63d9b', 
@@ -71,11 +67,9 @@ Multidialog contains audio and transcription data in English.
     '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).