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PaddleSpeech/examples/other/text_frontend/test_g2p.py

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# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import argparse
import re
from pathlib import Path
from parakeet.frontend.zh_frontend import Frontend as zhFrontend
from parakeet.utils.error_rate import word_errors
SILENCE_TOKENS = {"sp", "sil", "sp1", "spl"}
def text_cleaner(raw_text):
text = re.sub('#[1-4]|“|”||', '', raw_text)
text = text.replace("…。", "")
text = re.sub('||——|……|、|…|—', '', text)
return text
def get_avg_wer(raw_dict, ref_dict, frontend, output_dir):
edit_distances = []
ref_lens = []
wf_g2p = open(output_dir / "text.g2p", "w")
wf_ref = open(output_dir / "text.ref.clean", "w")
for utt_id in raw_dict:
if utt_id not in ref_dict:
continue
raw_text = raw_dict[utt_id]
text = text_cleaner(raw_text)
g2p_phones = frontend.get_phonemes(text)
g2p_phones = sum(g2p_phones, [])
gt_phones = ref_dict[utt_id].split(" ")
# delete silence tokens in predicted phones and ground truth phones
g2p_phones = [phn for phn in g2p_phones if phn not in SILENCE_TOKENS]
gt_phones = [phn for phn in gt_phones if phn not in SILENCE_TOKENS]
gt_phones = " ".join(gt_phones)
g2p_phones = " ".join(g2p_phones)
wf_ref.write(gt_phones + "(baker_" + utt_id + ")" + "\n")
wf_g2p.write(g2p_phones + "(baker_" + utt_id + ")" + "\n")
edit_distance, ref_len = word_errors(gt_phones, g2p_phones)
edit_distances.append(edit_distance)
ref_lens.append(ref_len)
return sum(edit_distances) / sum(ref_lens)
def main():
parser = argparse.ArgumentParser(description="g2p example.")
parser.add_argument(
"--input-dir",
default="data/g2p",
type=str,
help="directory to preprocessed test data.")
parser.add_argument(
"--output-dir",
default="exp/g2p",
type=str,
help="directory to save g2p results.")
args = parser.parse_args()
input_dir = Path(args.input_dir).expanduser()
output_dir = Path(args.output_dir).expanduser()
output_dir.mkdir(parents=True, exist_ok=True)
assert input_dir.is_dir()
raw_dict, ref_dict = dict(), dict()
raw_path = input_dir / "text"
ref_path = input_dir / "text.ref"
with open(raw_path, "r") as rf:
for line in rf:
line = line.strip()
line_list = line.split(" ")
utt_id, raw_text = line_list[0], " ".join(line_list[1:])
raw_dict[utt_id] = raw_text
with open(ref_path, "r") as rf:
for line in rf:
line = line.strip()
line_list = line.split(" ")
utt_id, phones = line_list[0], " ".join(line_list[1:])
ref_dict[utt_id] = phones
frontend = zhFrontend()
avg_wer = get_avg_wer(raw_dict, ref_dict, frontend, output_dir)
print("The avg WER of g2p is:", avg_wer)
if __name__ == "__main__":
main()