def METHOD_NAME():
    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 !")