Update MELD-Audio.py

MELD-Audio.py

@@ -1,7 +1,7 @@
 #!/usr/bin/env python3
 # -*- coding: utf-8 -*-
 """
-Created on Fri Apr 21 12:49:21 2023
+Created on Mon Apr 24 10:45:46 2023
 
 @author: lin.kinwahedward
 """
@@ -42,6 +42,7 @@ _HOMEPAGE = "https://affective-meld.github.io/"
 
 _LICENSE = "CC BY 4.0"
 
+# The actual place where the data is stored!
 _DATA_URL = "https://drive.google.com/uc?export=download&id=1TPr9v5Vz1qQuxPWcr8RedfuQvLyuG1lm"
 
 #------------------------------------------------------------------------------
@@ -72,16 +73,14 @@ class MELD_Audio(datasets.GeneratorBasedBuilder):
     #--------------------------------------------------------------------------
     '''
         Define the "column header" (feature) of a datum.
-        3 Features:
-            1) path_to_file
-            2) audio samples
-            3) emotion label
+        2 Features:
+            1) audio samples
+            2) emotion label
     '''
     def _info(self):
         
         features = datasets.Features(
                 {
-                    "path": datasets.Value("string"),
                     "audio": datasets.Audio(sampling_rate = 16000),
                     "label": datasets.ClassLabel(
                         names = [
@@ -105,9 +104,17 @@ class MELD_Audio(datasets.GeneratorBasedBuilder):
         )
     #--------------------------------------------------------------------------
     def _split_generators(self, dl_manager):
+        '''
+            Split the dataset into datasets.Split.{"TRAIN", "VALIDATION", "TEST", "ALL"}
+            
+            The dataset can be further modified, please see below link for details.            
+            https://huggingface.co/docs/datasets/process
+        '''
         
+        # Get the dataset and store at the machine where this script is executed!
         dataset_path = dl_manager.download_and_extract(self.config.data_url)
         
+        # "audio_path" and "csv_path" would be the parameters passed to def _generate_examples()
         return [
             datasets.SplitGenerator(
                     name = datasets.Split.TRAIN,
@@ -132,6 +139,8 @@ class MELD_Audio(datasets.GeneratorBasedBuilder):
     def _generate_examples(self, audio_path, csv_path):
         '''
             Get the audio file and set the corresponding labels
+            
+            Must execute till yield, otherwise, error will occur!
         '''
         key = 0
         with open(csv_path, encoding = "utf-8") as csv_file:
@@ -141,7 +150,6 @@ class MELD_Audio(datasets.GeneratorBasedBuilder):
                 _, _, _, emotion, _, dialogue_id, utterance_id, _, _, _, _ = row
                 filename = "dia" + dialogue_id + "_utt" + utterance_id + ".mp3"
                 yield key, {
-                    "path": audio_path + filename,
                     # huggingface dataset's will use soundfile to read the audio file
                     "audio": audio_path + filename,
                     "label": emotion,