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TTS/bin/remove_silence_using_vad.py

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+import argparse
+import glob
+import multiprocessing
+import os
+import pathlib
+
+import torch
+from tqdm import tqdm
+
+from TTS.utils.vad import get_vad_model_and_utils, remove_silence
+
+torch.set_num_threads(1)
+
+
+def adjust_path_and_remove_silence(audio_path):
+    output_path = audio_path.replace(os.path.join(args.input_dir, ""), os.path.join(args.output_dir, ""))
+    # ignore if the file exists
+    if os.path.exists(output_path) and not args.force:
+        return output_path, False
+
+    # create all directory structure
+    pathlib.Path(output_path).parent.mkdir(parents=True, exist_ok=True)
+    # remove the silence and save the audio
+    output_path, is_speech = remove_silence(
+        model_and_utils,
+        audio_path,
+        output_path,
+        trim_just_beginning_and_end=args.trim_just_beginning_and_end,
+        use_cuda=args.use_cuda,
+    )
+    return output_path, is_speech
+
+
+def preprocess_audios():
+    files = sorted(glob.glob(os.path.join(args.input_dir, args.glob), recursive=True))
+    print("> Number of files: ", len(files))
+    if not args.force:
+        print("> Ignoring files that already exist in the output idrectory.")
+
+    if args.trim_just_beginning_and_end:
+        print("> Trimming just the beginning and the end with nonspeech parts.")
+    else:
+        print("> Trimming all nonspeech parts.")
+
+    filtered_files = []
+    if files:
+        # create threads
+        # num_threads = multiprocessing.cpu_count()
+        # process_map(adjust_path_and_remove_silence, files, max_workers=num_threads, chunksize=15)
+
+        if args.num_processes > 1:
+            with multiprocessing.Pool(processes=args.num_processes) as pool:
+                results = list(
+                    tqdm(
+                        pool.imap_unordered(adjust_path_and_remove_silence, files),
+                        total=len(files),
+                        desc="Processing audio files",
+                    )
+                )
+            for output_path, is_speech in results:
+                if not is_speech:
+                    filtered_files.append(output_path)
+        else:
+            for f in tqdm(files):
+                output_path, is_speech = adjust_path_and_remove_silence(f)
+                if not is_speech:
+                    filtered_files.append(output_path)
+
+        # write files that do not have speech
+        with open(os.path.join(args.output_dir, "filtered_files.txt"), "w", encoding="utf-8") as f:
+            for file in filtered_files:
+                f.write(str(file) + "\n")
+    else:
+        print("> No files Found !")
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(
+        description="python TTS/bin/remove_silence_using_vad.py -i=VCTK-Corpus/ -o=VCTK-Corpus-removed-silence/ -g=wav48_silence_trimmed/*/*_mic1.flac --trim_just_beginning_and_end True"
+    )
+    parser.add_argument("-i", "--input_dir", type=str, help="Dataset root dir", required=True)
+    parser.add_argument("-o", "--output_dir", type=str, help="Output Dataset dir", default="")
+    parser.add_argument("-f", "--force", default=False, action="store_true", help="Force the replace of exists files")
+    parser.add_argument(
+        "-g",
+        "--glob",
+        type=str,
+        default="**/*.wav",
+        help="path in glob format for acess wavs from input_dir. ex: wav48/*/*.wav",
+    )
+    parser.add_argument(
+        "-t",
+        "--trim_just_beginning_and_end",
+        type=bool,
+        default=True,
+        help="If True this script will trim just the beginning and end nonspeech parts. If False all nonspeech parts will be trim. Default True",
+    )
+    parser.add_argument(
+        "-c",
+        "--use_cuda",
+        type=bool,
+        default=False,
+        help="If True use cuda",
+    )
+    parser.add_argument(
+        "--use_onnx",
+        type=bool,
+        default=False,
+        help="If True use onnx",
+    )
+    parser.add_argument(
+        "--num_processes",
+        type=int,
+        default=1,
+        help="Number of processes to use",
+    )
+    args = parser.parse_args()
+
+    if args.output_dir == "":
+        args.output_dir = args.input_dir
+
+    # load the model and utils
+    model_and_utils = get_vad_model_and_utils(use_cuda=args.use_cuda, use_onnx=args.use_onnx)
+    preprocess_audios()