File size: 2,756 Bytes
d2b34bb
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
import sys
from silero_vad import load_silero_vad
from silero_vad import read_audio , get_speech_timestamps , save_audio
from silero_vad import VADIterator , collect_chunks
import torch
import json
import os
import argparse
import logging
from pathlib import Path

logging.basicConfig(
    format="%(asctime)s | %(levelname)s | %(name)s | %(message)s",
    datefmt="%Y-%m-%d %H:%M:%S",
    level=os.environ.get("LOG_LEVEL", "INFO").upper())
LOGGER = logging.getLogger(__name__)

def main(args):
    parser = argparse.ArgumentParser(args)
    parser.add_argument("--folder", type=str, required=True, help="folder" )
    parser.add_argument("--sfx", type=str, required=False, default="wav",help="audio suffix" )
    parser.add_argument("--sr", type=int, required=False, default="16000",help="sampling rate" )
    parser.add_argument("--out_folder", type=str, required=False, default=None,help="output folder" )
    parser.add_argument("--out_file", type=str, required=True, help="json output" )
    parser.add_argument("--reverse", action="store_true", help="reverse processing order in folder")
    args = parser.parse_args()

    model = load_silero_vad(onnx=True)
    sr=args.sr
    out_folder=args.out_folder
    if out_folder:
        Path(out_folder).mkdir(parents=True, exist_ok=True)
        save_wav=True
    audio_list = sorted(os.listdir(args.folder),reverse=args.reverse)
    with open(args.out_file, "w") as outfile:
        for audiofile in audio_list:
            if audiofile.endswith(args.sfx):
                audiopath = os.path.join(args.folder, audiofile)
                audiofile = audiofile.replace(args.sfx,"wav")
                audio_id  = Path(audiofile).stem
                out_audio=f"{out_folder}/{audiofile}"
                if os.path.isfile(out_audio):
                    LOGGER.info(f"skipping {audiopath}")
                    continue
                LOGGER.info(f"processing {audiopath}")
                wav = read_audio(audiopath, sampling_rate=sr)
                speech_timestamps = get_speech_timestamps(wav, model, sampling_rate=sr)

                if speech_timestamps:
                    LOGGER.info(f"vad-processed {audiofile}: {len(speech_timestamps)} chunks")
                    for turn in speech_timestamps:
                        entry = {"audio_id": audio_id, "offset": turn['start']/sr, "duration":  (turn['end']-turn['start'])/sr}
                        json.dump(entry, outfile)
                        outfile.write('\n')
                    if save_wav:
                        save_audio(out_audio,collect_chunks(speech_timestamps, wav), sampling_rate=sr)
                        LOGGER.info(f"vad-processed {audiofile} written to {out_audio}")

if __name__ == '__main__':
    main(sys.argv)