# 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 json import os from paddle.utils.download import get_path_from_url from ..utils.env import DATA_HOME from .dataset 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://bj.bcebos.com/paddlenlp/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://bj.bcebos.com/paddlenlp/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}