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PaddleSpeech/deepspeech/utils/text_grid.py

128 lines
4.4 KiB

# 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.
from typing import Dict
from typing import List
from typing import Text
import textgrid
def segment_alignment(alignment: List[int], blank_id=0) -> List[List[int]]:
"""segment ctc alignment ids by continuous blank and repeat label.
Args:
alignment (List[int]): ctc alignment id sequence.
e.g. [0, 0, 0, 1, 1, 1, 2, 0, 0, 3]
blank_id (int, optional): blank id. Defaults to 0.
Returns:
List[List[int]]: token align, segment aligment id sequence.
e.g. [[0, 0, 0, 1, 1, 1], [2], [0, 0, 3]]
"""
# convert alignment to a praat format, which is a doing phonetics
# by computer and helps analyzing alignment
align_segs = []
# get frames level duration for each token
start = 0
end = 0
while end < len(alignment):
while end < len(alignment) and alignment[end] == blank_id: # blank
end += 1
if end == len(alignment):
align_segs[-1].extend(alignment[start:])
break
end += 1
while end < len(alignment) and alignment[end - 1] == alignment[
end]: # repeat label
end += 1
align_segs.append(alignment[start:end])
start = end
return align_segs
def align_to_tierformat(align_segs: List[List[int]],
subsample: int,
token_dict: Dict[int, Text],
blank_id=0) -> List[Text]:
"""Generate textgrid.Interval format from alignment segmentations.
Args:
align_segs (List[List[int]]): segmented ctc alignment ids.
subsample (int): 25ms frame_length, 10ms hop_length, 1/subsample
token_dict (Dict[int, Text]): int -> str map.
Returns:
List[Text]: list of textgrid.Interval text, str(start, end, text).
"""
hop_length = 10 # ms
second_ms = 1000 # ms
frame_per_second = second_ms / hop_length # 25ms frame_length, 10ms hop_length
second_per_frame = 1.0 / frame_per_second
begin = 0
duration = 0
tierformat = []
for idx, tokens in enumerate(align_segs):
token_len = len(tokens)
token = tokens[-1]
# time duration in second
duration = token_len * subsample * second_per_frame
if idx < len(align_segs) - 1:
print(f"{begin:.2f} {begin + duration:.2f} {token_dict[token]}")
tierformat.append(
f"{begin:.2f} {begin + duration:.2f} {token_dict[token]}\n")
else:
for i in tokens:
if i != blank_id:
token = i
break
print(f"{begin:.2f} {begin + duration:.2f} {token_dict[token]}")
tierformat.append(
f"{begin:.2f} {begin + duration:.2f} {token_dict[token]}\n")
begin = begin + duration
return tierformat
def generate_textgrid(maxtime: float,
intervals: List[Text],
output: Text,
name: Text='ali') -> None:
"""Create alignment textgrid file.
Args:
maxtime (float): audio duartion.
intervals (List[Text]): ctc output alignment. e.g. "start-time end-time word" per item.
output (Text): textgrid filepath.
name (Text, optional): tier or layer name. Defaults to 'ali'.
"""
# Download Praat: https://www.fon.hum.uva.nl/praat/
avg_interval = maxtime / (len(intervals) + 1)
print(f"average second/token: {avg_interval}")
margin = 0.0001
tg = textgrid.TextGrid(maxTime=maxtime)
tier = textgrid.IntervalTier(name=name, maxTime=maxtime)
i = 0
for dur in intervals:
s, e, text = dur.split()
tier.add(minTime=float(s) + margin, maxTime=float(e), mark=text)
tg.append(tier)
tg.write(output)
print("successfully generator textgrid {}.".format(output))