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* feat: add BSTC dataset * refactor: simplify code * docs: add BSTC dataset doc * docs: add doc to dataset_list.md * docs: rm data_prepare/dataset_list.rst Co-authored-by: Zeyu Chen <[email protected]>
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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 os | ||
|
|
||
| import json | ||
| from paddle.utils.download import get_path_from_url | ||
| from paddlenlp.utils.env import DATA_HOME | ||
| from . import DatasetBuilder | ||
|
|
||
|
|
||
| class BSTC(DatasetBuilder): | ||
| """ | ||
| BSTC (Baidu Speech Translation Corpus), a large-scale Chinese-English | ||
| speech translation dataset. This dataset is constructed based on a | ||
| collection of licensed videos of talks or lectures, including about | ||
| 68 hours of Mandarin data, their manual transcripts and translations | ||
| into English, as well as automated transcripts by an automatic speech | ||
| recognition (ASR) model. | ||
| Details: https://arxiv.org/pdf/2104.03575.pdf | ||
| """ | ||
| lazy = False | ||
| BUILDER_CONFIGS = { | ||
| 'transcription_translation': { | ||
| 'url': | ||
| "https://paddlenlp.bj.bcebos.com/datasets/bstc_transcription_translation.tar.gz", | ||
| 'md5': '236800188e397c42a3251982aeee48ee', | ||
| 'splits': { | ||
| 'train': | ||
| [os.path.join('bstc_transcription_translation', 'train')], | ||
| 'dev': [ | ||
| os.path.join('bstc_transcription_translation', 'dev', | ||
| 'streaming_transcription'), | ||
| os.path.join('bstc_transcription_translation', 'dev', | ||
| 'ref_text') | ||
| ] | ||
| } | ||
| }, | ||
| 'asr': { | ||
| 'url': "https://paddlenlp.bj.bcebos.com/datasets/bstc_asr.tar.gz", | ||
| 'md5': '3a0cc5039f45e62e29485e27d3a5f5a7', | ||
| 'splits': { | ||
| 'train': [os.path.join('bstc_asr', 'train', 'asr_sentences')], | ||
| 'dev': [ | ||
| os.path.join('bstc_asr', 'dev', 'streaming_asr'), | ||
| os.path.join('bstc_asr', 'dev', 'ref_text') | ||
| ] | ||
| } | ||
| } | ||
| } | ||
|
|
||
| def _get_data(self, mode, **kwargs): | ||
| ''' Check and download Dataset ''' | ||
| builder_config = self.BUILDER_CONFIGS[self.name] | ||
| default_root = os.path.join(DATA_HOME, self.__class__.__name__) | ||
| source_file_dir = builder_config['splits'][mode][0] | ||
| source_full_dir = os.path.join(default_root, source_file_dir) | ||
| if not os.path.exists(source_full_dir): | ||
| get_path_from_url(builder_config['url'], default_root, | ||
| builder_config['md5']) | ||
| if mode == 'train': | ||
| return source_full_dir | ||
| elif mode == 'dev': | ||
| target_file_dir = builder_config['splits'][mode][1] | ||
| target_full_dir = os.path.join(default_root, target_file_dir) | ||
| if not os.path.exists(target_full_dir): | ||
| get_path_from_url(builder_config['url'], default_root, | ||
| builder_config['md5']) | ||
| return source_full_dir, target_full_dir | ||
|
|
||
| def _read(self, data_dir, split): | ||
| """Reads data.""" | ||
| if split == 'train': | ||
| if self.name == 'transcription_translation': | ||
| source_full_dir = data_dir | ||
| filenames = [ | ||
| f for f in os.listdir(source_full_dir) | ||
| if not f.startswith('.') | ||
| ] | ||
| filenames.sort(key=lambda x: int(x[:-5])) | ||
| for filename in filenames: | ||
| with open( | ||
| os.path.join(source_full_dir, filename), | ||
| 'r', | ||
| encoding='utf-8') as f: | ||
| for line in f.readlines(): | ||
| line = line.strip() | ||
| if not line: | ||
| continue | ||
| yield json.loads(line) | ||
| elif self.name == 'asr': | ||
| source_full_dir = data_dir | ||
| dir_list = [ | ||
| f for f in os.listdir(source_full_dir) | ||
| if not f.startswith('.') | ||
| ] | ||
| dir_list.sort(key=lambda x: int(x)) | ||
| for dir_name in dir_list: | ||
| filenames = [ | ||
| f for f in | ||
| os.listdir(os.path.join(source_full_dir, dir_name)) | ||
| if not f.startswith('.') | ||
| ] | ||
| filenames.sort(key=lambda x: int(x[x.find('-') + 1:-5])) | ||
| for filename in filenames: | ||
| with open( | ||
| os.path.join(source_full_dir, dir_name, | ||
| filename), | ||
| 'r', | ||
| encoding='utf-8') as f: | ||
| for line in f.readlines(): | ||
| line = line.strip() | ||
| if not line: | ||
| continue | ||
| yield json.loads(line) | ||
| else: | ||
| raise ValueError( | ||
| 'Argument name should be one of [transcription_translation, asr].' | ||
| ) | ||
| elif split == 'dev': | ||
| source_full_dir, target_full_dir = data_dir | ||
| source_filenames = [ | ||
| f for f in os.listdir(source_full_dir) if f.endswith('txt') | ||
| ] | ||
| target_filenames = [ | ||
| f for f in os.listdir(target_full_dir) if f.endswith('txt') | ||
| ] | ||
| assert len(source_filenames) == len(target_filenames) | ||
| source_filenames.sort( | ||
| key=lambda x: int(x[:-4]) if self.name == 'transcription_translation' else int(x[:-8]) | ||
| ) | ||
| target_filenames.sort(key=lambda x: int(x[:-4])) | ||
| for src_file, tgt_file in zip(source_filenames, target_filenames): | ||
| if self.name == 'transcription_translation': | ||
| src_list = [] | ||
| with open( | ||
| os.path.join(source_full_dir, src_file), | ||
| 'r', | ||
| encoding='utf-8') as src_f: | ||
| src_part = [] | ||
| for src_line in src_f.readlines(): | ||
| src_line = src_line.strip() | ||
| if not src_line: | ||
| continue | ||
| if len(src_part) != 0 and not src_line.startswith( | ||
| src_part[-1]): | ||
| src_list.append(src_part) | ||
| src_part = [src_line] | ||
| else: | ||
| src_part.append(src_line) | ||
| if len(src_part) > 0: | ||
| src_list.append(src_part) | ||
| elif self.name == 'asr': | ||
| src_list = [] | ||
| with open( | ||
| os.path.join(source_full_dir, src_file), | ||
| 'r', | ||
| encoding='utf-8') as src_f: | ||
| src_part = [] | ||
| for src_line in src_f.readlines(): | ||
| src_line = src_line.strip() | ||
| if not src_line: | ||
| continue | ||
| line = src_line.split(', ') | ||
| final = line[2].split(': ')[1] == 'final' | ||
| src_part.append(src_line) | ||
| if final: | ||
| src_list.append(src_part) | ||
| src_part = [] | ||
| else: | ||
| raise ValueError( | ||
| 'Argument name should be one of [transcription_translation, asr].' | ||
| ) | ||
| tgt_list = [] | ||
| with open( | ||
| os.path.join(target_full_dir, tgt_file), | ||
| 'r', | ||
| encoding='utf-8') as tgt_f: | ||
| lines = tgt_f.readlines() | ||
| for idx, tgt_line in enumerate(lines): | ||
| tgt_line = tgt_line.strip() | ||
| if not tgt_line: | ||
| continue | ||
| tgt_list.append(tgt_line) | ||
| yield {'src': src_list, 'tgt': tgt_list} |