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