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97 lines
3.3 KiB
97 lines
3.3 KiB
#!/usr/bin/env python3
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# encoding: utf-8
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# Copyright 2017 Johns Hopkins University (Shinji Watanabe)
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# 2018 Xuankai Chang (Shanghai Jiao Tong University)
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# Apache 2.0 (http://www.apache.org/licenses/LICENSE-2.0)
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import argparse
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import json
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import logging
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import sys
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import jsonlines
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from utility import get_commandline_args
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def get_parser():
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parser = argparse.ArgumentParser(
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description="convert a json to a transcription file with a token dictionary",
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formatter_class=argparse.ArgumentDefaultsHelpFormatter, )
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parser.add_argument("json", type=str, help="jsonlines files")
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parser.add_argument("dict", type=str, help="dict, not used.")
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parser.add_argument(
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"--num-spkrs", type=int, default=1, help="number of speakers")
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parser.add_argument(
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"--refs", type=str, nargs="+", help="ref for all speakers")
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parser.add_argument(
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"--hyps", type=str, nargs="+", help="hyp for all outputs")
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return parser
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def main(args):
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args = get_parser().parse_args(args)
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convert(args.json, args.dict, args.refs, args.hyps, args.num_spkrs)
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def convert(jsonf, dic, refs, hyps, num_spkrs=1):
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n_ref = len(refs)
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n_hyp = len(hyps)
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assert n_ref == n_hyp
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assert n_ref == num_spkrs
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# logging info
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logfmt = "%(asctime)s (%(module)s:%(lineno)d) %(levelname)s: %(message)s"
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logging.basicConfig(level=logging.INFO, format=logfmt)
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logging.info(get_commandline_args())
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logging.info("reading %s", jsonf)
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with jsonlines.open(jsonf, "r") as f:
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j = [item for item in f]
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logging.info("reading %s", dic)
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with open(dic, "r") as f:
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dictionary = f.readlines()
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char_list = [entry.split(" ")[0] for entry in dictionary]
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char_list.insert(0, "<blank>")
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char_list.append("<eos>")
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for ns in range(num_spkrs):
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hyp_file = open(hyps[ns], "w")
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ref_file = open(refs[ns], "w")
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for x in j:
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# recognition hypothesis
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if num_spkrs == 1:
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#seq = [char_list[int(i)] for i in x['hyps_tokenid'][0]]
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seq = x['hyps'][0]
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else:
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seq = [char_list[int(i)] for i in x['hyps_tokenid'][ns]]
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# In the recognition hypothesis,
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# the <eos> symbol is usually attached in the last part of the sentence
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# and it is removed below.
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#hyp_file.write(" ".join(seq).replace("<eos>", ""))
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hyp_file.write(seq.replace("<eos>", ""))
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# spk-uttid
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hyp_file.write(" (" + x["utt"] + ")\n")
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# reference
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if num_spkrs == 1:
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seq = x["refs"][0]
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else:
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seq = x['refs'][ns]
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# Unlike the recognition hypothesis,
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# the reference is directly generated from a token without dictionary
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# to avoid to include <unk> symbols in the reference to make scoring normal.
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# The detailed discussion can be found at
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# https://github.com/espnet/espnet/issues/993
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# ref_file.write(
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# seq + " (" + j["utts"][x]["utt2spk"].replace("-", "_") + "-" + x + ")\n"
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# )
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ref_file.write(seq + " (" + x['utt'] + ")\n")
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hyp_file.close()
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ref_file.close()
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if __name__ == "__main__":
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main(sys.argv[1:])
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