init

push_s2t_translation.py

@@ -59,12 +59,14 @@ for i in tqdm(list(range(line_no_start, line_no_end))):
         continue
     i = loader(files[i])
     i[f"{direction_text}.text"] = line2text[str(i["line_no"])]
-    audio_file = i[f"{direction_speech}.path"]
+    audio_file = i.pop(f"{direction_speech}.path")
     start, end = i[f"{direction_speech}.duration_start"], i[f"{direction_speech}.duration_end"]
     if os.path.exists(audio_file):
         try:
             wav = audio_loader.decode_example({"path": audio_file, "bytes": None})
             if start < end < len(wav["array"]):
+                wav["array"] = wav["array"][start:end]
+                i[f"{direction_speech}.audio"] = wav
                 features.append(i)
             else:
                 delete_audio(audio_file)
@@ -74,34 +76,11 @@ for i in tqdm(list(range(line_no_start, line_no_end))):
 
 
 print(f"features (filtered): {len(features)}")
-data_dict = {f"{direction_speech}.audio": [i.pop(f"{direction_speech}.path") for i in features]}
 keys = features[0].keys()
-data_dict.update({k: [i[k] for i in features] for k in keys})
+data_dict = {k: [i[k] for i in features] for k in keys}
 audio_dataset = Dataset.from_dict(data_dict)
 audio_dataset = audio_dataset.cast_column(f"{direction_speech}.audio", Audio())
-
-
-# trim the audio according to the duration
-def clip_audio(batch):
-    start = batch[f"{direction_speech}.duration_start"]
-    end = batch[f"{direction_speech}.duration_end"]
-    audio = batch[f"{direction_speech}.audio"]
-    batch[f"{direction_speech}.audio"] = [
-        {"array": a["array"][s:e], "sampling_rate": a["sampling_rate"]}
-        for a, s, e in zip(audio, start, end)
-    ]
-    return batch
-
-
-audio_dataset_valid = audio_dataset_valid.map(
-    function=clip_audio,
-    batched=True,
-    batch_size=128,
-    num_proc=1,
-    desc="clipping audio based on the duration:"
-)
-
-dataset_to_push = DatasetDict({"train": audio_dataset_valid})
+dataset_to_push = DatasetDict({"train": audio_dataset})
 repo_name = f"{hf_org}/{hf_dataset}"
 while True:
     try: