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from collections import defaultdict |
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import os |
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import json |
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import csv |
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import datasets |
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_NAME="samromur_milljon" |
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_VERSION="1.0.0" |
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_AUDIO_EXTENSIONS=".flac" |
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_DESCRIPTION = """ |
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Samrómur Milljón consists of approximately 1 million of speech recordings (967 hours) collected through the platform samromur.is; the transcripts accompanying these recordings were automatically verified using various ASR systems such as: Wav2Vec, Whisper and NeMo. |
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""" |
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_CITATION = """ |
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@misc{menasamromurmilljon2023, |
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title={Samrómur Milljón, Audio and Transcriptions}, |
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author={Hernández Mena, Carlos Daniel and Guðnason, Jón}, |
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publisher={Reykjavík University} |
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year={2023}, |
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url={https://huggingface.co/datasets/language-and-voice-lab/samromur_milljon}, |
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} |
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""" |
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_HOMEPAGE = "https://huggingface.co/datasets/language-and-voice-lab/samromur_milljon" |
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_LICENSE = "CC-BY-4.0, See https://creativecommons.org/licenses/by/4.0/" |
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_BASE_DATA_DIR = "corpus/" |
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_METADATA_FEM_LT_18_YRS = os.path.join(_BASE_DATA_DIR,"files","metadata_fem_lt_18_yrs.tsv") |
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_METADATA_FEM_18TO49_YRS = os.path.join(_BASE_DATA_DIR,"files","metadata_fem_18to49_yrs.tsv") |
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_METADATA_FEM_GT_49_YRS = os.path.join(_BASE_DATA_DIR,"files","metadata_fem_gt_49_yrs.tsv") |
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_METADATA_MALE_LT_18_YRS = os.path.join(_BASE_DATA_DIR,"files","metadata_male_lt_18_yrs.tsv") |
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_METADATA_MALE_18TO49_YRS = os.path.join(_BASE_DATA_DIR,"files","metadata_male_18to49_yrs.tsv") |
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_METADATA_MALE_GT_49_YRS = os.path.join(_BASE_DATA_DIR,"files","metadata_male_gt_49_yrs.tsv") |
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_METADATA_OTHER = os.path.join(_BASE_DATA_DIR,"files","metadata_other.tsv") |
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_TARS_FEM_LT_18_YRS = os.path.join(_BASE_DATA_DIR,"files","tars_fem_lt_18_yrs.paths") |
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_TARS_FEM_18TO49_YRS = os.path.join(_BASE_DATA_DIR,"files","tars_fem_18to49_yrs.paths") |
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_TARS_FEM_GT_49_YRS = os.path.join(_BASE_DATA_DIR,"files","tars_fem_gt_49_yrs.paths") |
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_TARS_MALE_LT_18_YRS = os.path.join(_BASE_DATA_DIR,"files","tars_male_lt_18_yrs.paths") |
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_TARS_MALE_18TO49_YRS = os.path.join(_BASE_DATA_DIR,"files","tars_male_18to49_yrs.paths") |
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_TARS_MALE_GT_49_YRS = os.path.join(_BASE_DATA_DIR,"files","tars_male_gt_49_yrs.paths") |
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_TARS_OTHER = os.path.join(_BASE_DATA_DIR,"files","tars_other.paths") |
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class SamromurMilljonConfig(datasets.BuilderConfig): |
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"""BuilderConfig for The Samrómur Milljón""" |
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def __init__(self, name, **kwargs): |
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name=_NAME |
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super().__init__(name=name, **kwargs) |
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class SamromurMilljon(datasets.GeneratorBasedBuilder): |
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"""Samrómur Milljón""" |
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VERSION = datasets.Version(_VERSION) |
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BUILDER_CONFIGS = [ |
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SamromurMilljonConfig( |
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name=_NAME, |
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version=datasets.Version(_VERSION), |
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) |
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] |
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def _info(self): |
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features = datasets.Features( |
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{ |
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"audio_id": datasets.Value("string"), |
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"audio": datasets.Audio(sampling_rate=16000), |
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"speaker_id": datasets.Value("string"), |
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"gender": datasets.Value("string"), |
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"age": datasets.Value("string"), |
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"duration": datasets.Value("float32"), |
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"verified_with": datasets.Value("string"), |
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"normalized_text": datasets.Value("string"), |
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} |
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) |
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return datasets.DatasetInfo( |
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description=_DESCRIPTION, |
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features=features, |
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homepage=_HOMEPAGE, |
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license=_LICENSE, |
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citation=_CITATION, |
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) |
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def _split_generators(self, dl_manager): |
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metadata_fem_lt_18_yrs=dl_manager.download_and_extract(_METADATA_FEM_LT_18_YRS) |
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metadata_fem_18to49_yrs=dl_manager.download_and_extract(_METADATA_FEM_18TO49_YRS) |
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metadata_fem_gt_49_yrs=dl_manager.download_and_extract(_METADATA_FEM_GT_49_YRS) |
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metadata_male_lt_18_yrs=dl_manager.download_and_extract(_METADATA_MALE_LT_18_YRS) |
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metadata_male_18to49_yrs=dl_manager.download_and_extract(_METADATA_MALE_18TO49_YRS) |
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metadata_male_gt_49_yrs=dl_manager.download_and_extract(_METADATA_MALE_GT_49_YRS) |
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metadata_other=dl_manager.download_and_extract(_METADATA_OTHER) |
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tars_fem_lt_18_yrs=dl_manager.download_and_extract(_TARS_FEM_LT_18_YRS) |
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tars_fem_18to49_yrs=dl_manager.download_and_extract(_TARS_FEM_18TO49_YRS) |
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tars_fem_gt_49_yrs=dl_manager.download_and_extract(_TARS_FEM_GT_49_YRS) |
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tars_male_lt_18_yrs=dl_manager.download_and_extract(_TARS_MALE_LT_18_YRS) |
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tars_male_18to49_yrs=dl_manager.download_and_extract(_TARS_MALE_18TO49_YRS) |
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tars_male_gt_49_yrs=dl_manager.download_and_extract(_TARS_MALE_GT_49_YRS) |
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tars_other=dl_manager.download_and_extract(_TARS_OTHER) |
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hash_tar_files=defaultdict(dict) |
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with open(tars_fem_lt_18_yrs,'r') as f: |
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hash_tar_files['fem_lt_18_yrs']=[path.replace('\n','') for path in f] |
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with open(tars_fem_18to49_yrs,'r') as f: |
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hash_tar_files['fem_18to49_yrs']=[path.replace('\n','') for path in f] |
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with open(tars_fem_gt_49_yrs,'r') as f: |
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hash_tar_files['fem_gt_49_yrs']=[path.replace('\n','') for path in f] |
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with open(tars_male_lt_18_yrs,'r') as f: |
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hash_tar_files['male_lt_18_yrs']=[path.replace('\n','') for path in f] |
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with open(tars_male_18to49_yrs,'r') as f: |
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hash_tar_files['male_18to49_yrs']=[path.replace('\n','') for path in f] |
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with open(tars_male_gt_49_yrs,'r') as f: |
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hash_tar_files['male_gt_49_yrs']=[path.replace('\n','') for path in f] |
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with open(tars_other,'r') as f: |
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hash_tar_files['other']=[path.replace('\n','') for path in f] |
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hash_meta_paths={"fem_lt_18_yrs":metadata_fem_lt_18_yrs, |
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"fem_18to49_yrs":metadata_fem_18to49_yrs, |
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"fem_gt_49_yrs":metadata_fem_gt_49_yrs, |
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"male_lt_18_yrs":metadata_male_lt_18_yrs, |
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"male_18to49_yrs":metadata_male_18to49_yrs, |
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"male_gt_49_yrs":metadata_male_gt_49_yrs, |
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"other":metadata_other} |
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audio_paths = dl_manager.download(hash_tar_files) |
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splits=["fem_lt_18_yrs","fem_18to49_yrs","fem_gt_49_yrs","male_lt_18_yrs","male_18to49_yrs","male_gt_49_yrs","other"] |
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local_extracted_audio_paths = ( |
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dl_manager.extract(audio_paths) if not dl_manager.is_streaming else |
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{ |
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split:[None] * len(audio_paths[split]) for split in splits |
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} |
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) |
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return [ |
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datasets.SplitGenerator( |
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name="female_lt_18_yrs", |
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gen_kwargs={ |
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"audio_archives":[dl_manager.iter_archive(archive) for archive in audio_paths["fem_lt_18_yrs"]], |
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"local_extracted_archives_paths": local_extracted_audio_paths["fem_lt_18_yrs"], |
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"metadata_paths": hash_meta_paths["fem_lt_18_yrs"], |
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} |
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), |
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datasets.SplitGenerator( |
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name="female_18to49_yrs", |
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gen_kwargs={ |
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"audio_archives": [dl_manager.iter_archive(archive) for archive in audio_paths["fem_18to49_yrs"]], |
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"local_extracted_archives_paths": local_extracted_audio_paths["fem_18to49_yrs"], |
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"metadata_paths": hash_meta_paths["fem_18to49_yrs"], |
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} |
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), |
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datasets.SplitGenerator( |
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name="female_gt_49_yrs", |
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gen_kwargs={ |
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"audio_archives": [dl_manager.iter_archive(archive) for archive in audio_paths["fem_gt_49_yrs"]], |
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"local_extracted_archives_paths": local_extracted_audio_paths["fem_gt_49_yrs"], |
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"metadata_paths": hash_meta_paths["fem_gt_49_yrs"], |
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} |
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), |
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datasets.SplitGenerator( |
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name="male_lt_18_yrs", |
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gen_kwargs={ |
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"audio_archives":[dl_manager.iter_archive(archive) for archive in audio_paths["male_lt_18_yrs"]], |
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"local_extracted_archives_paths": local_extracted_audio_paths["male_lt_18_yrs"], |
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"metadata_paths": hash_meta_paths["male_lt_18_yrs"], |
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} |
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), |
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datasets.SplitGenerator( |
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name="male_18to49_yrs", |
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gen_kwargs={ |
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"audio_archives": [dl_manager.iter_archive(archive) for archive in audio_paths["male_18to49_yrs"]], |
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"local_extracted_archives_paths": local_extracted_audio_paths["male_18to49_yrs"], |
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"metadata_paths": hash_meta_paths["male_18to49_yrs"], |
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} |
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), |
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datasets.SplitGenerator( |
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name="male_gt_49_yrs", |
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gen_kwargs={ |
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"audio_archives": [dl_manager.iter_archive(archive) for archive in audio_paths["male_gt_49_yrs"]], |
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"local_extracted_archives_paths": local_extracted_audio_paths["male_gt_49_yrs"], |
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"metadata_paths": hash_meta_paths["male_gt_49_yrs"], |
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} |
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), |
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datasets.SplitGenerator( |
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name="other", |
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gen_kwargs={ |
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"audio_archives": [dl_manager.iter_archive(archive) for archive in audio_paths["other"]], |
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"local_extracted_archives_paths": local_extracted_audio_paths["other"], |
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"metadata_paths": hash_meta_paths["other"], |
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} |
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), |
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] |
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def _generate_examples(self, audio_archives, local_extracted_archives_paths, metadata_paths): |
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features = ["speaker_id","gender","age","duration","verified_with","normalized_text"] |
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with open(metadata_paths) as f: |
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metadata = {x["audio_id"]: x for x in csv.DictReader(f, delimiter="\t")} |
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for audio_archive, local_extracted_archive_path in zip(audio_archives, local_extracted_archives_paths): |
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for audio_filename, audio_file in audio_archive: |
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audio_id =os.path.splitext(os.path.basename(audio_filename))[0] |
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path = os.path.join(local_extracted_archive_path, audio_filename) if local_extracted_archive_path else audio_filename |
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yield audio_id, { |
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"audio_id": audio_id, |
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**{feature: metadata[audio_id][feature] for feature in features}, |
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"audio": {"path": path, "bytes": audio_file.read()}, |
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} |
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