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trim_silence.py
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executable file
·116 lines (96 loc) · 3.48 KB
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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Copyright 2018 Nagoya University (Tomoki Hayashi)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
from __future__ import division
import argparse
import codecs
import logging
import os
import kaldiio
import librosa
import matplotlib.pyplot as plt
import numpy
from espnet.utils.cli_utils import get_commandline_args
def _time_to_str(time_idx):
time_idx = time_idx * 10 ** 4
return "%06d" % time_idx
def get_parser():
parser = argparse.ArgumentParser(
description="Trim slience with simple power thresholding "
"and make segments file.",
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
)
parser.add_argument("--fs", type=int, help="Sampling frequency")
parser.add_argument(
"--threshold", type=float, default=60, help="Threshold in decibels"
)
parser.add_argument(
"--win_length", type=int, default=1024, help="Analisys window length in point"
)
parser.add_argument(
"--shift_length", type=int, default=256, help="Shift length in point"
)
parser.add_argument(
"--min_silence", type=float, default=0.01, help="minimum silence length"
)
parser.add_argument(
"--figdir", type=str, default="figs", help="Directory to save figures"
)
parser.add_argument("--verbose", "-V", default=0, type=int, help="Verbose option")
parser.add_argument(
"--normalize",
choices=[1, 16, 24, 32],
type=int,
default=None,
help="Give the bit depth of the PCM, "
"then normalizes data to scale in [-1,1]",
)
parser.add_argument("rspecifier", type=str, help="WAV scp file")
parser.add_argument("wspecifier", type=str, help="Segments file")
return parser
def main():
parser = get_parser()
args = parser.parse_args()
# set logger
logfmt = "%(asctime)s (%(module)s:%(lineno)d) %(levelname)s: %(message)s"
if args.verbose > 0:
logging.basicConfig(level=logging.INFO, format=logfmt)
else:
logging.basicConfig(level=logging.WARN, format=logfmt)
logging.info(get_commandline_args())
if not os.path.exists(args.figdir):
os.makedirs(args.figdir)
with kaldiio.ReadHelper(args.rspecifier) as reader, codecs.open(
args.wspecifier, "w", encoding="utf-8"
) as f:
for utt_id, (rate, array) in reader:
assert rate == args.fs
array = array.astype(numpy.float32)
if args.normalize is not None and args.normalize != 1:
array = array / (1 << (args.normalize - 1))
array_trim, idx = librosa.effects.trim(
y=array,
top_db=args.threshold,
frame_length=args.win_length,
hop_length=args.shift_length,
)
start, end = idx / args.fs
# save figure
plt.subplot(2, 1, 1)
plt.plot(array)
plt.title("Original")
plt.subplot(2, 1, 2)
plt.plot(array_trim)
plt.title("Trim")
plt.tight_layout()
plt.savefig(args.figdir + "/" + utt_id + ".png")
plt.close()
# added minimum silence part
start = max(0.0, start - args.min_silence)
end = min(len(array) / args.fs, end + args.min_silence)
# write to segments file
segment = "%s %s %f %f\n" % (utt_id, utt_id, start, end)
f.write(segment)
if __name__ == "__main__":
main()