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138 lines
4.4 KiB
138 lines
4.4 KiB
#!/usr/bin/env python3
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# prend un fichier audio et imprime des sous titres au format srt
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from vosk import Model, KaldiRecognizer, SetLogLevel
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import sys
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import os
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import subprocess
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import json
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import argparse
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from collections import namedtuple
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from pprint import pprint
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import time
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try:
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from tqdm import tqdm
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tqdm_installed = True
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except:
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tqdm_installed = False
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start_time = time.time()
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MODEL_LANG="fr"
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class SubPart:
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def __init__(self, start, end, text):
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self.start = start
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self.end = end
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self.text = text
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@staticmethod
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def ftot(f):
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h = int(f//3600)
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m = int(f//60 % 60)
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s = int(f//1 % 60)
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ms = int((1000 * f) % 1000)
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s = f"{h:02}:{m:02}:{s:02},{ms:03}"
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return s
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def __repr__(self):
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return f"""
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{self.ftot(self.start)} --> {self.ftot(self.end)}
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{self.text}
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"""[1:-1]
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def gen_subparts(input_file, model_dir, verbose=False, partlen=4, progress=True):
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SetLogLevel(0 if verbose else -1)
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model = Model(model_dir)
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rec = KaldiRecognizer(model, 16000)
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process = subprocess.Popen(['ffmpeg', '-loglevel', 'quiet', '-i',
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input_file,
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'-ar', str(16000) , '-ac', '1', '-f', 's16le', '-'],
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stdout=subprocess.PIPE)
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r = subprocess.run("ffprobe -v error -show_entries format=duration -of default=noprint_wrappers=1:nokey=1".split() + [input_file], stdout=subprocess.PIPE)
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duration = float(r.stdout.decode('utf-8').strip())
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if progress:
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pbar = tqdm(total=duration, unit="s")
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prev_end = 0
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while True:
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data = process.stdout.read(4000)
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if len(data) == 0:
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break
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if rec.AcceptWaveform(data):
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r = json.loads(rec.Result())
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if 'result' in r:
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resultpart = [] # TODO: use this across AccesptForm
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for result in r['result']:
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if len(resultpart) > 0 and float(result['end']) - float(resultpart[0]['start']) >= partlen:
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yield SubPart(start=resultpart[0]['start'],
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end=float(resultpart[-1]['end']),
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text=" ".join(r['word'] for r in resultpart))
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prev_end = float(resultpart[-1]['end'])
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resultpart = []
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if float(result['end'] - result['start']) >= partlen:
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yield SubPart(start=float(result['start']),
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end=float(result['end']),
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text=result['word'])
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prev_end = float(result['end'])
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resultpart = []
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else:
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resultpart.append(result)
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if progress:
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pbar.update(float(result['end'] - pbar.n))
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if len(resultpart) > 0:
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yield SubPart(start=float(resultpart[0]['start']),
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end=float(resultpart[-1]['end']),
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text=" ".join(r['word'] for r in resultpart))
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prev_end = float(resultpart[-1]['end'])
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resultpart = []
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else:
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pass
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#print(rec.PartialResult())
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# pprint(rec.PartialResult())
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if progress:
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pbar.close()
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r = json.loads(rec.PartialResult())
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text = r['partial']
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yield SubPart(start=prev_end, end=duration, text=text)
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def create_parser():
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parser = argparse.ArgumentParser(prog="SRT file extractor using Speech-To-Text")
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parser.add_argument("-v", "--verbose", action="store_true")
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parser.add_argument("-o", "--output", type=argparse.FileType('w+'), default=sys.stdout)
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parser.add_argument("-m", "--model", required=False)
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parser.add_argument("-i", "--interval", default=4)
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if tqdm_installed:
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parser.add_argument("-p", "--progress", action="store_true")
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parser.add_argument("input")
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return parser
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def main():
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args = create_parser().parse_args()
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if tqdm_installed:
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it = enumerate(gen_subparts(args.input, "models/"+MODEL_LANG, args.verbose, args.interval, args.progress))
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else:
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it = enumerate(gen_subparts(args.input, "models/"+MODEL_LANG, args.verbose, args.interval, False))
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for i,subpart in it:
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n = i+1
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args.output.write(f"""{n}
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{subpart}
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"""
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)
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if __name__ == "__main__":
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main()
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