You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
PaddleSpeech/utils/json2trn.py

97 lines
3.3 KiB

#!/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 json
import logging
import sys
import jsonlines
from utility 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="jsonlines files")
parser.add_argument("dict", type=str, help="dict, not used.")
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 jsonlines.open(jsonf, "r") as f:
j = [item for item in f]
logging.info("reading %s", dic)
with open(dic, "r") 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 = open(hyps[ns], "w")
ref_file = open(refs[ns], "w")
for x in j:
# recognition hypothesis
if num_spkrs == 1:
#seq = [char_list[int(i)] for i in x['hyps_tokenid'][0]]
seq = x['hyps'][0]
else:
seq = [char_list[int(i)] for i in x['hyps_tokenid'][ns]]
# 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(seq.replace("<eos>", ""))
# spk-uttid
hyp_file.write(" (" + x["utt"] + ")\n")
# reference
if num_spkrs == 1:
seq = x["refs"][0]
else:
seq = x['refs'][ns]
# 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"
# )
ref_file.write(seq + " (" + x['utt'] + ")\n")
hyp_file.close()
ref_file.close()
if __name__ == "__main__":
main(sys.argv[1:])