File size: 3,436 Bytes
d596074 |
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 99 100 101 102 103 104 105 106 107 |
# Copyright 2021 Xiaomi Corp. (authors: Fangjun Kuang,
# Wei Kang)
#
# See ../../LICENSE for clarification regarding multiple authors
#
# 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 re
from typing import List
import k2
import torch
from icefall.lexicon import Lexicon
class CharCtcTrainingGraphCompiler(object):
def __init__(
self,
lexicon: Lexicon,
device: torch.device,
sos_token: str = "<sos/eos>",
eos_token: str = "<sos/eos>",
oov: str = "<unk>",
):
"""
Args:
lexicon:
It is built from `data/lang_char/lexicon.txt`.
device:
The device to use for operations compiling transcripts to FSAs.
oov:
Out of vocabulary token. When a word(token) in the transcript
does not exist in the token list, it is replaced with `oov`.
"""
assert oov in lexicon.token_table
self.oov_id = lexicon.token_table[oov]
self.token_table = lexicon.token_table
self.device = device
self.sos_id = self.token_table[sos_token]
self.eos_id = self.token_table[eos_token]
def texts_to_ids(self, texts: List[str], sep: str = "") -> List[List[int]]:
"""Convert a list of texts to a list-of-list of token IDs.
Args:
texts:
It is a list of strings.
An example containing two strings is given below:
['你好中国', '北京欢迎您']
sep:
The separator of the items in one sequence, mainly no separator for
Chinese (one character a token), "/" for Chinese characters plus BPE
token and pinyin tokens.
Returns:
Return a list-of-list of token IDs.
"""
assert sep in ("", "/"), sep
ids: List[List[int]] = []
whitespace = re.compile(r"([ \t])")
for text in texts:
if sep == "":
text = re.sub(whitespace, "", text)
else:
text = text.split(sep)
sub_ids = [
self.token_table[txt] if txt in self.token_table else self.oov_id
for txt in text
]
ids.append(sub_ids)
return ids
def compile(
self,
token_ids: List[List[int]],
modified: bool = False,
) -> k2.Fsa:
"""Build a ctc graph from a list-of-list token IDs.
Args:
piece_ids:
It is a list-of-list integer IDs.
modified:
See :func:`k2.ctc_graph` for its meaning.
Return:
Return an FsaVec, which is the result of composing a
CTC topology with linear FSAs constructed from the given
piece IDs.
"""
graph = k2.ctc_graph(token_ids, modified=modified, device=self.device)
return graph
|