# MIT License
#
# Copyright (c) 2021 Soohwan Kim and Sangchun Ha and Soyoung Cho
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in all
# copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
import csv
from omegaconf import DictConfig
from dataclasses import dataclass, field
from openspeech.dataclass.configurations import TokenizerConfigs
from openspeech.tokenizers import register_tokenizer
from openspeech.tokenizers.tokenizer import Tokenizer
[docs]@dataclass
class KsponSpeechCharacterTokenizerConfigs(TokenizerConfigs):
unit: str = field(
default="kspon_character", metadata={"help": "Unit of vocabulary."}
)
vocab_path: str = field(
default="../../../aihub_labels.csv", metadata={"help": "Path of vocabulary file."}
)
[docs]@register_tokenizer("kspon_character", dataclass=KsponSpeechCharacterTokenizerConfigs)
class KsponSpeechCharacterTokenizer(Tokenizer):
r"""
Tokenizer class in Character-units for KsponSpeech.
Args:
configs (DictConfig): configuration set.
"""
def __init__(self, configs: DictConfig):
super(KsponSpeechCharacterTokenizer, self).__init__()
self.vocab_dict, self.id_dict = self.load_vocab(
vocab_path=configs.tokenizer.vocab_path,
encoding=configs.tokenizer.encoding,
)
self.labels = self.vocab_dict.keys()
self.sos_id = int(self.vocab_dict[configs.tokenizer.sos_token])
self.eos_id = int(self.vocab_dict[configs.tokenizer.eos_token])
self.pad_id = int(self.vocab_dict[configs.tokenizer.pad_token])
self.blank_id = int(self.vocab_dict[configs.tokenizer.blank_token])
self.vocab_path = configs.tokenizer.vocab_path
def __len__(self):
return len(self.labels)
[docs] def decode(self, labels):
r"""
Converts label to string (number => Hangeul)
Args:
labels (numpy.ndarray): number label
Returns: sentence
- **sentence** (str or list): symbol of labels
"""
if len(labels.shape) == 1:
sentence = str()
for label in labels:
if label.item() == self.eos_id:
break
elif label.item() == self.blank_id:
continue
sentence += self.id_dict[label.item()]
return sentence
sentences = list()
for batch in labels:
sentence = str()
for label in batch:
if label.item() == self.eos_id:
break
elif label.item() == self.blank_id:
continue
sentence += self.id_dict[label.item()]
sentences.append(sentence)
return sentences
def encode(self, sentence):
label = str()
for ch in sentence:
try:
label += (str(self.vocab_dict[ch]) + ' ')
except KeyError:
continue
return label[:-1]
[docs] def load_vocab(self, vocab_path, encoding='utf-8'):
r"""
Provides char2id, id2char
Args:
vocab_path (str): csv file with character labels
encoding (str): encoding method
Returns: unit2id, id2unit
- **unit2id** (dict): unit2id[unit] = id
- **id2unit** (dict): id2unit[id] = unit
"""
unit2id = dict()
id2unit = dict()
try:
with open(vocab_path, 'r', encoding=encoding) as f:
labels = csv.reader(f, delimiter=',')
next(labels)
for row in labels:
unit2id[row[1]] = row[0]
id2unit[int(row[0])] = row[1]
return unit2id, id2unit
except IOError:
raise IOError("Character label file (csv format) doesn`t exist : {0}".format(vocab_path))