Datasets:
ArXiv:
License:
| import os | |
| from pathlib import Path | |
| from typing import Dict, List, Tuple | |
| from zipfile import ZipFile | |
| import datasets | |
| import yaml | |
| from seacrowd.utils import schemas | |
| from seacrowd.utils.configs import SEACrowdConfig | |
| from seacrowd.utils.constants import Licenses, Tasks | |
| _CITATION = """\ | |
| @inproceedings{PhoST, | |
| title = {{A High-Quality and Large-Scale Dataset for English-Vietnamese Speech Translation}}, | |
| author = {Linh The Nguyen and Nguyen Luong Tran and Long Doan and Manh Luong and Dat Quoc Nguyen}, | |
| booktitle = {Proceedings of the 23rd Annual Conference of the International Speech Communication Association (INTERSPEECH)}, | |
| year = {2022} | |
| } | |
| """ | |
| _DATASETNAME = "phost" | |
| _DESCRIPTION = """\ | |
| PhoST is a high-quality and large-scale benchmark dataset for English-Vietnamese speech translation | |
| with 508 audio hours, consisting of 331K triplets of (sentence-lengthed audio, English source | |
| transcript sentence, Vietnamese target subtitle sentence). | |
| """ | |
| _HOMEPAGE = "https://github.com/VinAIResearch/PhoST" | |
| _LICENSE = Licenses.CC_BY_NC_ND_4_0.value | |
| _LOCAL = True | |
| _SUPPORTED_TASKS = [Tasks.SPEECH_RECOGNITION, Tasks.SPEECH_TO_TEXT_TRANSLATION, Tasks.MACHINE_TRANSLATION] | |
| _SOURCE_VERSION = "1.0.0" | |
| _SEACROWD_VERSION = "2024.06.20" | |
| _LANGUAGES = ["eng", "vie"] | |
| def seacrowd_config_constructor(src_lang, tgt_lang, schema, version): | |
| if src_lang == "" or tgt_lang == "": | |
| raise ValueError(f"Invalid src_lang {src_lang} or tgt_lang {tgt_lang}") | |
| if schema not in ["source", "seacrowd_sptext", "seacrowd_t2t"]: | |
| raise ValueError(f"Invalid schema: {schema}") | |
| return SEACrowdConfig( | |
| name="phost_{src}_{tgt}_{schema}".format(src=src_lang, tgt=tgt_lang, schema=schema), | |
| version=datasets.Version(version), | |
| description="phost schema for {schema} from {src} to {tgt}".format(schema=schema, src=src_lang, tgt=tgt_lang), | |
| schema=schema, | |
| subset_id="phost_{src}_{tgt}".format(src=src_lang, tgt=tgt_lang), | |
| ) | |
| class Phost(datasets.GeneratorBasedBuilder): | |
| """ | |
| PhoST is a high-quality and large-scale benchmark dataset for English-Vietnamese speech translation | |
| with 508 audio hours, consisting of 331K triplets of (sentence-lengthed audio, English source | |
| transcript sentence, Vietnamese target subtitle sentence). | |
| """ | |
| SOURCE_VERSION = datasets.Version(_SOURCE_VERSION) | |
| SEACROWD_VERSION = datasets.Version(_SEACROWD_VERSION) | |
| BUILDER_CONFIGS = [ | |
| seacrowd_config_constructor("en", "vi", "source", _SOURCE_VERSION), | |
| seacrowd_config_constructor("en", "vi", "seacrowd_sptext", _SEACROWD_VERSION), | |
| seacrowd_config_constructor("en", "vi", "seacrowd_t2t", _SEACROWD_VERSION), | |
| ] | |
| DEFAULT_CONFIG_NAME = "phost_en_vi_source" | |
| def _info(self) -> datasets.DatasetInfo: | |
| if self.config.schema == "source": | |
| features = datasets.Features( | |
| { | |
| "file": datasets.Value("string"), | |
| "audio": datasets.Audio(sampling_rate=16_000), | |
| "en_text": datasets.Value("string"), | |
| "vi_text": datasets.Value("string"), | |
| "timing": datasets.Sequence(datasets.Value("string")), | |
| } | |
| ) | |
| elif self.config.schema == "seacrowd_sptext": | |
| features = schemas.speech_text_features | |
| elif self.config.schema == "seacrowd_t2t": | |
| features = schemas.text2text_features | |
| return datasets.DatasetInfo( | |
| description=_DESCRIPTION, | |
| features=features, | |
| homepage=_HOMEPAGE, | |
| license=_LICENSE, | |
| citation=_CITATION, | |
| ) | |
| def _split_generators(self, dl_manager: datasets.DownloadManager) -> List[datasets.SplitGenerator]: | |
| """Returns SplitGenerators.""" | |
| if self.config.data_dir is None: | |
| raise ValueError("This is a local dataset. Please pass the data_dir kwarg to load_dataset.") | |
| else: | |
| data_dir = self.config.data_dir | |
| aud_path = os.path.join(data_dir, "audio_data") | |
| if not os.path.exists(aud_path): | |
| os.makedirs(aud_path) | |
| # loading the temp.zip and creating a zip object | |
| with ZipFile(os.path.join(data_dir, "train_audio.zip"), "r") as zObject: | |
| for member in zObject.namelist(): | |
| if not os.path.exists(os.path.join(aud_path, "train", member)) or not os.path.isfile(os.path.join(aud_path, "train", member)): | |
| zObject.extract(member, os.path.join(aud_path, "train")) | |
| # dev audio files | |
| with ZipFile(os.path.join(data_dir, "dev_audio.zip"), "r") as zObject: | |
| for member in zObject.namelist(): | |
| if not os.path.exists(os.path.join(aud_path, "dev", member)) or not os.path.isfile(os.path.join(aud_path, "dev", member)): | |
| zObject.extract(member, aud_path) | |
| # test audio files | |
| with ZipFile(os.path.join(data_dir, "test_audio.zip"), "r") as zObject: | |
| for member in zObject.namelist(): | |
| if not os.path.exists(os.path.join(aud_path, "test", member)) or not os.path.isfile(os.path.join(aud_path, "test", member)): | |
| zObject.extract(member, aud_path) | |
| # text data | |
| with ZipFile(os.path.join(data_dir, "text_data.zip"), "r") as zObject: | |
| for member in zObject.namelist(): | |
| if not os.path.exists(os.path.join(data_dir, member)) or not os.path.isfile(os.path.join(data_dir, member)): | |
| zObject.extract(member, data_dir) | |
| return [ | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TRAIN, | |
| gen_kwargs={ | |
| "filepath": {"audio": os.path.join(aud_path, "train", "wav"), "text": os.path.join(data_dir, "text_data", "train")}, | |
| "split": "train", | |
| }, | |
| ), | |
| datasets.SplitGenerator( | |
| name=datasets.Split.TEST, | |
| gen_kwargs={ | |
| "filepath": {"audio": os.path.join(aud_path, "test", "wav"), "text": os.path.join(data_dir, "text_data", "test")}, | |
| "split": "test", | |
| }, | |
| ), | |
| datasets.SplitGenerator( | |
| name=datasets.Split.VALIDATION, | |
| gen_kwargs={ | |
| "filepath": {"audio": os.path.join(aud_path, "dev", "wav"), "text": os.path.join(data_dir, "text_data", "dev")}, | |
| "split": "dev", | |
| }, | |
| ), | |
| ] | |
| def _generate_examples(self, filepath: Path, split: str) -> Tuple[int, Dict]: | |
| """Yields examples as (key, example) tuples.""" | |
| config_names_split = self.config.name.split("_") | |
| src_lang = config_names_split[1] | |
| tgt_lang = config_names_split[2] | |
| track_ids = os.listdir(filepath["text"]) | |
| timing = [] | |
| en_sub = [] | |
| vi_sub = [] | |
| counter = 0 | |
| for key, track_id in enumerate(track_ids): | |
| with open(os.path.join(filepath["text"], track_id, track_id + ".yaml")) as timing_file: | |
| timing = yaml.safe_load(timing_file) | |
| with open(os.path.join(filepath["text"], track_id, track_id + ".en")) as en_text: | |
| en_sub = [line.strip() for line in en_text] | |
| with open( | |
| os.path.join(filepath["text"], track_id, track_id + ".vi"), | |
| ) as vi_text: | |
| vi_sub = [line.strip() for line in vi_text] | |
| if self.config.schema == "source": | |
| yield key, {"file": os.path.join(filepath["audio"], track_id + ".wav"), "audio": os.path.join(filepath["audio"], track_id + ".wav"), "en_text": " ".join(en_sub), "vi_text": " ".join(vi_sub), "timing": timing} | |
| elif self.config.schema == "seacrowd_sptext": | |
| if tgt_lang not in ["en", "vi"]: | |
| raise NotImplementedError(f"Target language '{tgt_lang}' is not defined.") | |
| yield key, { | |
| "id": track_id, | |
| "path": os.path.join(filepath["audio"], track_id + ".wav"), | |
| "audio": os.path.join(filepath["audio"], track_id + ".wav"), | |
| "text": " ".join(en_sub) if tgt_lang == "en" else " ".join(vi_sub), | |
| "speaker_id": None, | |
| "metadata": { | |
| "speaker_age": None, | |
| "speaker_gender": None, | |
| }, | |
| } | |
| elif self.config.schema == "seacrowd_t2t": | |
| if src_lang not in ["en", "vi"]: | |
| raise NotImplementedError(f"Source language '{src_lang}' is not defined.") | |
| if tgt_lang not in ["en", "vi"]: | |
| raise NotImplementedError(f"Target language '{tgt_lang}' is not defined.") | |
| for en_line, vi_line in zip(en_sub, vi_sub): | |
| yield counter, { | |
| "id": f"{track_id}_{str(counter)}", | |
| "text_1": en_line if src_lang == "en" else vi_line, | |
| "text_2": en_line if tgt_lang == "en" else vi_line, | |
| "text_1_name": src_lang, | |
| "text_2_name": tgt_lang, | |
| } | |
| counter += 1 | |
| else: | |
| raise NotImplementedError(f"Schema '{self.config.schema}' is not defined.") | |