process all examples

voxpopuli.py

@@ -2,7 +2,6 @@ from collections import defaultdict
 import os
 import glob
 import csv
-from pathlib import Path
 from tqdm.auto import tqdm
 
 import datasets
@@ -67,7 +66,7 @@ class Voxpopuli(datasets.GeneratorBasedBuilder):
         for name in _LANGUAGES + ["10k", "100k", "400k"]
     ]
     # DEFAULT_CONFIG_NAME = "400k"
-    # DEFAULT_WRITER_BATCH_SIZE = 1
+    # DEFAULT_WRITER_BATCH_SIZE = 256
 
     def _info(self):
         features = datasets.Features(
@@ -137,7 +136,7 @@ class Voxpopuli(datasets.GeneratorBasedBuilder):
         metadata = self._read_metadata(metadata_path)
 
         for data_dir in data_dirs:
-            for file in glob.glob(f"{data_dir}/**/*.ogg", recursive=True)[:5]:
+            for file in glob.glob(f"{data_dir}/**/*.ogg", recursive=True):
                 path_components = file.split(os.sep)
                 language, year, audio_filename = path_components[-3:]
                 audio_id, _ = os.path.splitext(audio_filename)
@@ -146,6 +145,7 @@ class Voxpopuli(datasets.GeneratorBasedBuilder):
                 waveform, sr = torchaudio.load(file)
                 duration = waveform.size(1)
 
+                # split audio on the fly and write segments as arrays
                 for segment_id, (start, stop) in enumerate(timestamps):
                     segment = waveform[:, int(start * sr): min(int(stop * sr), duration)]