mirror of
https://github.com/k2-fsa/icefall.git
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ece728d895
* add init files * fix bug, apply delay penalty * fix decoding code and getting timestamps * add option applying delay penalty on ctc log-prob * fix bug of streaming decoding * minor change for bpe-based case * add test_model.py * add README.md * add CI
122 lines
3.8 KiB
Python
122 lines
3.8 KiB
Python
# Copyright 2021 Xiaomi Corp. (authors: Fangjun Kuang,
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# Wei Kang)
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#
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# See ../../LICENSE for clarification regarding multiple authors
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import re
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from typing import List
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import k2
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import torch
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from icefall.lexicon import Lexicon
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class CharCtcTrainingGraphCompiler(object):
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def __init__(
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self,
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lexicon: Lexicon,
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device: torch.device,
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sos_token: str = "<sos/eos>",
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eos_token: str = "<sos/eos>",
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oov: str = "<unk>",
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):
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"""
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Args:
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lexicon:
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It is built from `data/lang_char/lexicon.txt`.
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device:
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The device to use for operations compiling transcripts to FSAs.
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oov:
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Out of vocabulary token. When a word(token) in the transcript
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does not exist in the token list, it is replaced with `oov`.
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"""
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assert oov in lexicon.token_table
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self.oov_id = lexicon.token_table[oov]
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self.token_table = lexicon.token_table
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self.device = device
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self.sos_id = self.token_table[sos_token]
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self.eos_id = self.token_table[eos_token]
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def texts_to_ids(self, texts: List[str]) -> List[List[int]]:
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"""Convert a list of texts to a list-of-list of token IDs.
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Args:
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texts:
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It is a list of strings.
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An example containing two strings is given below:
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['你好中国', '北京欢迎您']
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Returns:
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Return a list-of-list of token IDs.
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"""
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ids: List[List[int]] = []
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whitespace = re.compile(r"([ \t])")
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for text in texts:
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text = re.sub(whitespace, "", text)
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sub_ids = [
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self.token_table[txt] if txt in self.token_table else self.oov_id
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for txt in text
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]
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ids.append(sub_ids)
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return ids
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def texts_to_ids_with_bpe(self, texts: List[str]) -> List[List[int]]:
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"""Convert a list of texts (which include chars and bpes)
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to a list-of-list of token IDs.
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Args:
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texts:
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It is a list of strings.
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An example containing two strings is given below:
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[['你', '好', '▁C', 'hina'], ['北','京', '▁', 'welcome', '您']
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Returns:
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Return a list-of-list of token IDs.
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"""
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ids: List[List[int]] = []
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for text in texts:
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text = text.split("/")
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sub_ids = [
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self.token_table[txt] if txt in self.token_table else self.oov_id
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for txt in text
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]
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ids.append(sub_ids)
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return ids
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def compile(
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self,
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token_ids: List[List[int]],
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modified: bool = False,
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) -> k2.Fsa:
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"""Build a ctc graph from a list-of-list token IDs.
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Args:
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piece_ids:
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It is a list-of-list integer IDs.
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modified:
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See :func:`k2.ctc_graph` for its meaning.
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Return:
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Return an FsaVec, which is the result of composing a
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CTC topology with linear FSAs constructed from the given
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piece IDs.
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"""
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graph = k2.ctc_graph(token_ids, modified=modified, device=self.device)
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return graph
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