Update NURC-SP_ENTOA_TTS.py

NURC-SP_ENTOA_TTS.py

@@ -1,8 +1,11 @@
 import csv
 import datasets
 from datasets import BuilderConfig, GeneratorBasedBuilder, DatasetInfo, SplitGenerator, Split
+import logging
 
-
+# Set up logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
 
 _PROMPTS_URLS = {
     "dev": "automatic/validation.csv",
@@ -24,13 +27,11 @@ _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"),
@@ -62,13 +63,19 @@ class NurcSPDataset(GeneratorBasedBuilder):
         )
 
     def _split_generators(self, dl_manager):
-        prompts_urls = _PROMPTS_URLS  # Default to original prompts URLs
-
+        logger.info(f"Using prompts_type: {self.config.prompts_type}")
+        
+        prompts_urls = _PROMPTS_URLS
         if self.config.prompts_type == "filtered":
             prompts_urls = _PROMPTS_FILTERED_URLS
-
+        
+        logger.info(f"Downloading prompts from: {prompts_urls}")
         prompts_path = dl_manager.download(prompts_urls)
+        logger.info(f"Downloaded prompts to: {prompts_path}")
+        
+        logger.info(f"Downloading archives from: {_ARCHIVES}")
         archive = dl_manager.download(_ARCHIVES)
+        logger.info(f"Downloaded archives to: {archive}")
 
         return [
             SplitGenerator(
@@ -90,50 +97,54 @@ class NurcSPDataset(GeneratorBasedBuilder):
         ]
 
     def _generate_examples(self, prompts_path, path_to_clips, audio_files):
+        logger.info(f"Generating examples from prompts_path: {prompts_path}")
+        logger.info(f"Looking for clips in: {path_to_clips}")
+        
         examples = {}
+        example_count = 0
+        
+        # Read CSV file
         with open(prompts_path, "r") 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']] = {
+                    "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'],
                 }
+                example_count += 1
+        
+        logger.info(f"Found {example_count} examples in CSV")
+        
         inside_clips_dir = False
         id_ = 0
+        matched_files = 0
+        
         for path, f in audio_files:
+            logger.debug(f"Processing archive file: {path}")
             if path.startswith(path_to_clips):
                 inside_clips_dir = True
+                logger.debug(f"Found file in clips directory: {path}")
                 if path in examples:
                     audio = {"path": path, "bytes": f.read()}
+                    matched_files += 1
                     yield id_, {**examples[path], "audio": audio}
                     id_ += 1
             elif inside_clips_dir:
-                break
+                break
+        
+        logger.info(f"Matched {matched_files} audio files with CSV entries")
+        if matched_files == 0:
+            logger.warning("No audio files were matched with CSV entries!")