forked from espnet/espnet
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Copy pathjson2trn.py
executable file
·100 lines (82 loc) · 3.44 KB
/
json2trn.py
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
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
#!/usr/bin/env python3
# encoding: utf-8
# Copyright 2017 Johns Hopkins University (Shinji Watanabe)
# 2018 Xuankai Chang (Shanghai Jiao Tong University)
# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
import argparse
import codecs
import json
import logging
import sys
from espnet.utils.cli_utils import get_commandline_args
def get_parser():
parser = argparse.ArgumentParser(
description="convert a json to a transcription file with a token dictionary",
formatter_class=argparse.ArgumentDefaultsHelpFormatter,
)
parser.add_argument("json", type=str, help="json files")
parser.add_argument("dict", type=str, help="dict")
parser.add_argument("--num-spkrs", type=int, default=1, help="number of speakers")
parser.add_argument("--refs", type=str, nargs="+", help="ref for all speakers")
parser.add_argument("--hyps", type=str, nargs="+", help="hyp for all outputs")
return parser
def main(args):
args = get_parser().parse_args(args)
convert(args.json, args.dict, args.refs, args.hyps, args.num_spkrs)
def convert(jsonf, dic, refs, hyps, num_spkrs=1):
n_ref = len(refs)
n_hyp = len(hyps)
assert n_ref == n_hyp
assert n_ref == num_spkrs
# logging info
logfmt = "%(asctime)s (%(module)s:%(lineno)d) %(levelname)s: %(message)s"
logging.basicConfig(level=logging.INFO, format=logfmt)
logging.info(get_commandline_args())
logging.info("reading %s", jsonf)
with codecs.open(jsonf, "r", encoding="utf-8") as f:
j = json.load(f)
logging.info("reading %s", dic)
with codecs.open(dic, "r", encoding="utf-8") as f:
dictionary = f.readlines()
char_list = [entry.split(" ")[0] for entry in dictionary]
char_list.insert(0, "<blank>")
char_list.append("<eos>")
for ns in range(num_spkrs):
hyp_file = codecs.open(hyps[ns], "w", encoding="utf-8")
ref_file = codecs.open(refs[ns], "w", encoding="utf-8")
for x in j["utts"]:
# recognition hypothesis
if num_spkrs == 1:
seq = [
char_list[int(i)]
for i in j["utts"][x]["output"][0]["rec_tokenid"].split()
]
else:
seq = [
char_list[int(i)]
for i in j["utts"][x]["output"][ns][0]["rec_tokenid"].split()
]
# In the recognition hypothesis,
# the <eos> symbol is usually attached in the last part of the sentence
# and it is removed below.
hyp_file.write(" ".join(seq).replace("<eos>", "")),
hyp_file.write(
" (" + j["utts"][x]["utt2spk"].replace("-", "_") + "-" + x + ")\n"
)
# reference
if num_spkrs == 1:
seq = j["utts"][x]["output"][0]["token"]
else:
seq = j["utts"][x]["output"][ns][0]["token"]
# Unlike the recognition hypothesis,
# the reference is directly generated from a token without dictionary
# to avoid to include <unk> symbols in the reference to make scoring normal.
# The detailed discussion can be found at
# https://github.com/espnet/espnet/issues/993
ref_file.write(
seq + " (" + j["utts"][x]["utt2spk"].replace("-", "_") + "-" + x + ")\n"
)
hyp_file.close()
ref_file.close()
if __name__ == "__main__":
main(sys.argv[1:])