Create preprocess.py

data/preprocess.py

@@ -0,0 +1,39 @@
+import csv
+import os
+import tarfile
+from hashlib import sha1
+
+
+def hexdigest(string):
+    return sha1(string.encode()).hexdigest()
+
+
+def read_fairseq(root, subset):
+    with open(f"{root}/{subset}/train.tsv", 'r') as tsv, open(f"{root}/{subset}/train.wrd", 'r') as wrd:
+        audio = map(lambda x: x[0], csv.reader(tsv, delimiter='\t'))
+        transcriptions = map(lambda x: x.strip(), wrd.readlines())
+        metadata = [[path, hexdigest(transcription), transcription]
+                    for path, transcription in zip(audio, transcriptions)]
+    return metadata[1:]
+
+
+def shard_wav_files(file_paths, shard_size_limit, output_dir, arcnames=None):
+    shard_index = 1
+    current_shard_size = 0
+    current_tar = None
+
+    for i, file_path in enumerate(file_paths):
+        file_size = os.path.getsize(file_path)
+
+        if not current_tar or current_shard_size + file_size > shard_size_limit:
+            if current_tar: current_tar.close()
+            shard_name = f"shard_{shard_index}.tar"
+            shard_path = os.path.join(output_dir, shard_name)
+            current_tar = tarfile.open(shard_path, "w")
+            shard_index += 1
+            current_shard_size = 0
+
+        current_tar.add(file_path, arcname=arcnames[i] if arcnames else os.path.basename(file_path))
+        current_shard_size += file_size
+
+    if current_tar: current_tar.close()