Update NURC-SP_ENTOA_TTS.py

NURC-SP_ENTOA_TTS.py

@@ -2,8 +2,6 @@ import csv
 import datasets
 from datasets import BuilderConfig, GeneratorBasedBuilder, DatasetInfo, SplitGenerator, Split
 
-
-
 _PROMPTS_URLS = {
     "dev": "automatic/validation.csv",
     "train": "automatic/train.csv",
@@ -24,13 +22,11 @@ _PATH_TO_CLIPS = {
     "train": "train",
 }
 
-
 class NurcSPConfig(BuilderConfig):
     def __init__(self, prompts_type="original", **kwargs):
         super().__init__(**kwargs)
         self.prompts_type = prompts_type
 
-
 class NurcSPDataset(GeneratorBasedBuilder):
     BUILDER_CONFIGS = [
         NurcSPConfig(name="original", description="Original audio prompts", prompts_type="original"),
@@ -62,78 +58,52 @@ class NurcSPDataset(GeneratorBasedBuilder):
         )
 
     def _split_generators(self, dl_manager):
-        prompts_urls = _PROMPTS_URLS  # Default to original prompts URLs
-
-        if self.config.prompts_type == "filtered":
-            prompts_urls = _PROMPTS_FILTERED_URLS
-
-        prompts_path = dl_manager.download(prompts_urls)
-        archive = dl_manager.download(_ARCHIVES)
+        prompts_urls = _PROMPTS_URLS if self.config.prompts_type == "original" else _PROMPTS_FILTERED_URLS
+        
+        # Download the prompts CSV files and audio archive
+        prompts_path = dl_manager.download_and_extract(prompts_urls)
+        archive = dl_manager.download_and_extract(_ARCHIVES)
 
+        # Return split generators
         return [
             SplitGenerator(
-                name=Split.VALIDATION,
+                name=Split.TRAIN,
                 gen_kwargs={
-                    "prompts_path": prompts_path["dev"],
-                    "path_to_clips": _PATH_TO_CLIPS["dev"],
-                    "audio_files": dl_manager.iter_archive(archive["dev"]),
+                    "prompts_path": prompts_path["train"],
+                    "path_to_clips": _PATH_TO_CLIPS["train"],
+                    "audio_files": archive["train"],
                 }
             ),
             SplitGenerator(
-                name=Split.TRAIN,
+                name=Split.VALIDATION,  # Changed from Split.VALIDATION to match error message
                 gen_kwargs={
-                    "prompts_path": prompts_path["train"],
-                    "path_to_clips": _PATH_TO_CLIPS["train"],
-                    "audio_files": dl_manager.iter_archive(archive["train"]),
+                    "prompts_path": prompts_path["dev"],
+                    "path_to_clips": _PATH_TO_CLIPS["dev"],
+                    "audio_files": archive["dev"],
                 }
             ),
         ]
 
     def _generate_examples(self, prompts_path, path_to_clips, audio_files):
+        # Load CSV data
         examples = {}
-        with open(prompts_path, "r") as f:
+        with open(prompts_path, "r", encoding='utf-8') as f:
             csv_reader = csv.DictReader(f)
             for row in csv_reader:
-                audio_name = row['audio_name']
-                file_path = row['file_path']
-                text = row['text']
-                start_time = row['start_time']
-                end_time = row['end_time']
-                duration = row['duration']
-                quality = row['quality']
-                speech_genre = row['speech_genre']
-                speech_style = row['speech_style']
-                variety = row['variety']
-                accent = row['accent']
-                sex = row['sex']
-                age_range = row['age_range']
-                num_speakers = row['num_speakers']
-                speaker_id = row['speaker_id']
-                examples[file_path] = {
-                    "audio_name": audio_name,
-                    "file_path": file_path,
-                    "text": text,
-                    "start_time": start_time,
-                    "end_time": end_time,
-                    "duration": duration,
-                    "quality": quality,
-                    "speech_genre": speech_genre,
-                    "speech_style": speech_style,
-                    "variety": variety,
-                    "accent": accent,
-                    "sex": sex,
-                    "age_range": age_range,
-                    "num_speakers": num_speakers,
-                    "speaker_id": speaker_id,
+                examples[row['file_path']] = {
+                    key: row[key] 
+                    for key in row.keys()
                 }
-        inside_clips_dir = False
+
+        # Process audio files
         id_ = 0
-        for path, f in audio_files:
-            if path.startswith(path_to_clips):
-                inside_clips_dir = True
-                if path in examples:
-                    audio = {"path": path, "bytes": f.read()}
-                    yield id_, {**examples[path], "audio": audio}
-                    id_ += 1
-            elif inside_clips_dir:
-                break
+        for root, _, files in datasets.utils.py_utils.walk(audio_files):
+            if path_to_clips in root:
+                for fname in files:
+                    file_path = f"{path_to_clips}/{fname}"
+                    if file_path in examples:
+                        full_path = f"{root}/{fname}"
+                        with open(full_path, "rb") as audio_file:
+                            audio = {"path": file_path, "bytes": audio_file.read()}
+                            yield id_, {**examples[file_path], "audio": audio}
+                            id_ += 1