common_voice / common_voice.py
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Update common_voice.py (#4212)
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# coding=utf-8
# Copyright 2021 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# 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.
""" Common Voice Dataset"""
import os
import datasets
from datasets.tasks import AutomaticSpeechRecognition
_DATA_URL = "https://voice-prod-bundler-ee1969a6ce8178826482b88e843c335139bd3fb4.s3.amazonaws.com/cv-corpus-6.1-2020-12-11/{}.tar.gz"
_CITATION = """\
@inproceedings{commonvoice:2020,
author = {Ardila, R. and Branson, M. and Davis, K. and Henretty, M. and Kohler, M. and Meyer, J. and Morais, R. and Saunders, L. and Tyers, F. M. and Weber, G.},
title = {Common Voice: A Massively-Multilingual Speech Corpus},
booktitle = {Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020)},
pages = {4211--4215},
year = 2020
}
"""
_DESCRIPTION = """\
Common Voice is Mozilla's initiative to help teach machines how real people speak.
The dataset currently consists of 7,335 validated hours of speech in 60 languages, but we’re always adding more voices and languages.
"""
_HOMEPAGE = "https://commonvoice.mozilla.org/en/datasets"
_LICENSE = "https://github.com/common-voice/common-voice/blob/main/LICENSE"
_LANGUAGES = {
"ab": {
"Language": "Abkhaz",
"Date": "2020-12-11",
"Size": "39 MB",
"Version": "ab_1h_2020-12-11",
"Validated_Hr_Total": 0.05,
"Overall_Hr_Total": 1,
"Number_Of_Voice": 14,
},
"ar": {
"Language": "Arabic",
"Date": "2020-12-11",
"Size": "2 GB",
"Version": "ar_77h_2020-12-11",
"Validated_Hr_Total": 49,
"Overall_Hr_Total": 77,
"Number_Of_Voice": 672,
},
"as": {
"Language": "Assamese",
"Date": "2020-12-11",
"Size": "21 MB",
"Version": "as_0.78h_2020-12-11",
"Validated_Hr_Total": 0.74,
"Overall_Hr_Total": 0.78,
"Number_Of_Voice": 17,
},
"br": {
"Language": "Breton",
"Date": "2020-12-11",
"Size": "444 MB",
"Version": "br_16h_2020-12-11",
"Validated_Hr_Total": 7,
"Overall_Hr_Total": 16,
"Number_Of_Voice": 157,
},
"ca": {
"Language": "Catalan",
"Date": "2020-12-11",
"Size": "19 GB",
"Version": "ca_748h_2020-12-11",
"Validated_Hr_Total": 623,
"Overall_Hr_Total": 748,
"Number_Of_Voice": 5376,
},
"cnh": {
"Language": "Hakha Chin",
"Date": "2020-12-11",
"Size": "39 MB",
"Version": "ab_1h_2020-12-11",
"Validated_Hr_Total": 0.05,
"Overall_Hr_Total": 1,
"Number_Of_Voice": 14,
},
"cs": {
"Language": "Czech",
"Date": "2020-12-11",
"Size": "39 MB",
"Version": "ab_1h_2020-12-11",
"Validated_Hr_Total": 0.05,
"Overall_Hr_Total": 1,
"Number_Of_Voice": 14,
},
"cv": {
"Language": "Chuvash",
"Date": "2020-12-11",
"Size": "419 MB",
"Version": "cv_16h_2020-12-11",
"Validated_Hr_Total": 4,
"Overall_Hr_Total": 16,
"Number_Of_Voice": 92,
},
"cy": {
"Language": "Welsh",
"Date": "2020-12-11",
"Size": "3 GB",
"Version": "cy_124h_2020-12-11",
"Validated_Hr_Total": 95,
"Overall_Hr_Total": 124,
"Number_Of_Voice": 1382,
},
"de": {
"Language": "German",
"Date": "2020-12-11",
"Size": "22 GB",
"Version": "de_836h_2020-12-11",
"Validated_Hr_Total": 777,
"Overall_Hr_Total": 836,
"Number_Of_Voice": 12659,
},
"dv": {
"Language": "Dhivehi",
"Date": "2020-12-11",
"Size": "515 MB",
"Version": "dv_19h_2020-12-11",
"Validated_Hr_Total": 18,
"Overall_Hr_Total": 19,
"Number_Of_Voice": 167,
},
"el": {
"Language": "Greek",
"Date": "2020-12-11",
"Size": "364 MB",
"Version": "el_13h_2020-12-11",
"Validated_Hr_Total": 6,
"Overall_Hr_Total": 13,
"Number_Of_Voice": 118,
},
"en": {
"Language": "English",
"Date": "2020-12-11",
"Size": "56 GB",
"Version": "en_2181h_2020-12-11",
"Validated_Hr_Total": 1686,
"Overall_Hr_Total": 2181,
"Number_Of_Voice": 66173,
},
"eo": {
"Language": "Esperanto",
"Date": "2020-12-11",
"Size": "3 GB",
"Version": "eo_102h_2020-12-11",
"Validated_Hr_Total": 90,
"Overall_Hr_Total": 102,
"Number_Of_Voice": 574,
},
"es": {
"Language": "Spanish",
"Date": "2020-12-11",
"Size": "15 GB",
"Version": "es_579h_2020-12-11",
"Validated_Hr_Total": 324,
"Overall_Hr_Total": 579,
"Number_Of_Voice": 19484,
},
"et": {
"Language": "Estonian",
"Date": "2020-12-11",
"Size": "732 MB",
"Version": "et_27h_2020-12-11",
"Validated_Hr_Total": 19,
"Overall_Hr_Total": 27,
"Number_Of_Voice": 543,
},
"eu": {
"Language": "Basque",
"Date": "2020-12-11",
"Size": "3 GB",
"Version": "eu_131h_2020-12-11",
"Validated_Hr_Total": 89,
"Overall_Hr_Total": 131,
"Number_Of_Voice": 1028,
},
"fa": {
"Language": "Persian",
"Date": "2020-12-11",
"Size": "8 GB",
"Version": "fa_321h_2020-12-11",
"Validated_Hr_Total": 282,
"Overall_Hr_Total": 321,
"Number_Of_Voice": 3655,
},
"fi": {
"Language": "Finnish",
"Date": "2020-12-11",
"Size": "48 MB",
"Version": "fi_1h_2020-12-11",
"Validated_Hr_Total": 1,
"Overall_Hr_Total": 1,
"Number_Of_Voice": 27,
},
"fr": {
"Language": "French",
"Date": "2020-12-11",
"Size": "18 GB",
"Version": "fr_682h_2020-12-11",
"Validated_Hr_Total": 623,
"Overall_Hr_Total": 682,
"Number_Of_Voice": 12953,
},
"fy-NL": {
"Language": "Frisian",
"Date": "2020-12-11",
"Size": "1 GB",
"Version": "fy-NL_46h_2020-12-11",
"Validated_Hr_Total": 14,
"Overall_Hr_Total": 46,
"Number_Of_Voice": 467,
},
"ga-IE": {
"Language": "Irish",
"Date": "2020-12-11",
"Size": "149 MB",
"Version": "ga-IE_5h_2020-12-11",
"Validated_Hr_Total": 3,
"Overall_Hr_Total": 5,
"Number_Of_Voice": 101,
},
"hi": {
"Language": "Hindi",
"Date": "2020-12-11",
"Size": "20 MB",
"Version": "hi_0.8h_2020-12-11",
"Validated_Hr_Total": 0.54,
"Overall_Hr_Total": 0.8,
"Number_Of_Voice": 31,
},
"hsb": {
"Language": "Sorbian, Upper",
"Date": "2020-12-11",
"Size": "76 MB",
"Version": "hsb_2h_2020-12-11",
"Validated_Hr_Total": 2,
"Overall_Hr_Total": 2,
"Number_Of_Voice": 19,
},
"hu": {
"Language": "Hungarian",
"Date": "2020-12-11",
"Size": "232 MB",
"Version": "hu_8h_2020-12-11",
"Validated_Hr_Total": 8,
"Overall_Hr_Total": 8,
"Number_Of_Voice": 47,
},
"ia": {
"Language": "InterLinguia",
"Date": "2020-12-11",
"Size": "216 MB",
"Version": "ia_8h_2020-12-11",
"Validated_Hr_Total": 6,
"Overall_Hr_Total": 8,
"Number_Of_Voice": 36,
},
"id": {
"Language": "Indonesian",
"Date": "2020-12-11",
"Size": "454 MB",
"Version": "id_17h_2020-12-11",
"Validated_Hr_Total": 9,
"Overall_Hr_Total": 17,
"Number_Of_Voice": 219,
},
"it": {
"Language": "Italian",
"Date": "2020-12-11",
"Size": "5 GB",
"Version": "it_199h_2020-12-11",
"Validated_Hr_Total": 158,
"Overall_Hr_Total": 199,
"Number_Of_Voice": 5729,
},
"ja": {
"Language": "Japanese",
"Date": "2020-12-11",
"Size": "146 MB",
"Version": "ja_5h_2020-12-11",
"Validated_Hr_Total": 3,
"Overall_Hr_Total": 5,
"Number_Of_Voice": 235,
},
"ka": {
"Language": "Georgian",
"Date": "2020-12-11",
"Size": "99 MB",
"Version": "ka_3h_2020-12-11",
"Validated_Hr_Total": 3,
"Overall_Hr_Total": 3,
"Number_Of_Voice": 44,
},
"kab": {
"Language": "Kabyle",
"Date": "2020-12-11",
"Size": "16 GB",
"Version": "kab_622h_2020-12-11",
"Validated_Hr_Total": 525,
"Overall_Hr_Total": 622,
"Number_Of_Voice": 1309,
},
"ky": {
"Language": "Kyrgyz",
"Date": "2020-12-11",
"Size": "553 MB",
"Version": "ky_22h_2020-12-11",
"Validated_Hr_Total": 11,
"Overall_Hr_Total": 22,
"Number_Of_Voice": 134,
},
"lg": {
"Language": "Luganda",
"Date": "2020-12-11",
"Size": "199 MB",
"Version": "lg_8h_2020-12-11",
"Validated_Hr_Total": 3,
"Overall_Hr_Total": 8,
"Number_Of_Voice": 76,
},
"lt": {
"Language": "Lithuanian",
"Date": "2020-12-11",
"Size": "129 MB",
"Version": "lt_4h_2020-12-11",
"Validated_Hr_Total": 2,
"Overall_Hr_Total": 4,
"Number_Of_Voice": 30,
},
"lv": {
"Language": "Latvian",
"Date": "2020-12-11",
"Size": "199 MB",
"Version": "lv_7h_2020-12-11",
"Validated_Hr_Total": 6,
"Overall_Hr_Total": 7,
"Number_Of_Voice": 99,
},
"mn": {
"Language": "Mongolian",
"Date": "2020-12-11",
"Size": "464 MB",
"Version": "mn_17h_2020-12-11",
"Validated_Hr_Total": 11,
"Overall_Hr_Total": 17,
"Number_Of_Voice": 376,
},
"mt": {
"Language": "Maltese",
"Date": "2020-12-11",
"Size": "405 MB",
"Version": "mt_15h_2020-12-11",
"Validated_Hr_Total": 7,
"Overall_Hr_Total": 15,
"Number_Of_Voice": 171,
},
"nl": {
"Language": "Dutch",
"Date": "2020-12-11",
"Size": "2 GB",
"Version": "nl_63h_2020-12-11",
"Validated_Hr_Total": 59,
"Overall_Hr_Total": 63,
"Number_Of_Voice": 1012,
},
"or": {
"Language": "Odia",
"Date": "2020-12-11",
"Size": "190 MB",
"Version": "or_7h_2020-12-11",
"Validated_Hr_Total": 0.87,
"Overall_Hr_Total": 7,
"Number_Of_Voice": 34,
},
"pa-IN": {
"Language": "Punjabi",
"Date": "2020-12-11",
"Size": "67 MB",
"Version": "pa-IN_2h_2020-12-11",
"Validated_Hr_Total": 0.5,
"Overall_Hr_Total": 2,
"Number_Of_Voice": 26,
},
"pl": {
"Language": "Polish",
"Date": "2020-12-11",
"Size": "3 GB",
"Version": "pl_129h_2020-12-11",
"Validated_Hr_Total": 108,
"Overall_Hr_Total": 129,
"Number_Of_Voice": 2647,
},
"pt": {
"Language": "Portuguese",
"Date": "2020-12-11",
"Size": "2 GB",
"Version": "pt_63h_2020-12-11",
"Validated_Hr_Total": 50,
"Overall_Hr_Total": 63,
"Number_Of_Voice": 1120,
},
"rm-sursilv": {
"Language": "Romansh Sursilvan",
"Date": "2020-12-11",
"Size": "263 MB",
"Version": "rm-sursilv_9h_2020-12-11",
"Validated_Hr_Total": 5,
"Overall_Hr_Total": 9,
"Number_Of_Voice": 78,
},
"rm-vallader": {
"Language": "Romansh Vallader",
"Date": "2020-12-11",
"Size": "103 MB",
"Version": "rm-vallader_3h_2020-12-11",
"Validated_Hr_Total": 2,
"Overall_Hr_Total": 3,
"Number_Of_Voice": 39,
},
"ro": {
"Language": "Romanian",
"Date": "2020-12-11",
"Size": "250 MB",
"Version": "ro_9h_2020-12-11",
"Validated_Hr_Total": 6,
"Overall_Hr_Total": 9,
"Number_Of_Voice": 130,
},
"ru": {
"Language": "Russian",
"Date": "2020-12-11",
"Size": "3 GB",
"Version": "ru_130h_2020-12-11",
"Validated_Hr_Total": 111,
"Overall_Hr_Total": 130,
"Number_Of_Voice": 1412,
},
"rw": {
"Language": "Kinyarwanda",
"Date": "2020-12-11",
"Size": "40 GB",
"Version": "rw_1510h_2020-12-11",
"Validated_Hr_Total": 1183,
"Overall_Hr_Total": 1510,
"Number_Of_Voice": 410,
},
"sah": {
"Language": "Sakha",
"Date": "2020-12-11",
"Size": "173 MB",
"Version": "sah_6h_2020-12-11",
"Validated_Hr_Total": 4,
"Overall_Hr_Total": 6,
"Number_Of_Voice": 42,
},
"sl": {
"Language": "Slovenian",
"Date": "2020-12-11",
"Size": "212 MB",
"Version": "sl_7h_2020-12-11",
"Validated_Hr_Total": 5,
"Overall_Hr_Total": 7,
"Number_Of_Voice": 82,
},
"sv-SE": {
"Language": "Swedish",
"Date": "2020-12-11",
"Size": "402 MB",
"Version": "sv-SE_15h_2020-12-11",
"Validated_Hr_Total": 12,
"Overall_Hr_Total": 15,
"Number_Of_Voice": 222,
},
"ta": {
"Language": "Tamil",
"Date": "2020-12-11",
"Size": "648 MB",
"Version": "ta_24h_2020-12-11",
"Validated_Hr_Total": 14,
"Overall_Hr_Total": 24,
"Number_Of_Voice": 266,
},
"th": {
"Language": "Thai",
"Date": "2020-12-11",
"Size": "325 MB",
"Version": "th_12h_2020-12-11",
"Validated_Hr_Total": 8,
"Overall_Hr_Total": 12,
"Number_Of_Voice": 182,
},
"tr": {
"Language": "Turkish",
"Date": "2020-12-11",
"Size": "592 MB",
"Version": "tr_22h_2020-12-11",
"Validated_Hr_Total": 20,
"Overall_Hr_Total": 22,
"Number_Of_Voice": 678,
},
"tt": {
"Language": "Tatar",
"Date": "2020-12-11",
"Size": "741 MB",
"Version": "tt_28h_2020-12-11",
"Validated_Hr_Total": 26,
"Overall_Hr_Total": 28,
"Number_Of_Voice": 185,
},
"uk": {
"Language": "Ukrainian",
"Date": "2020-12-11",
"Size": "1 GB",
"Version": "uk_43h_2020-12-11",
"Validated_Hr_Total": 30,
"Overall_Hr_Total": 43,
"Number_Of_Voice": 459,
},
"vi": {
"Language": "Vietnamese",
"Date": "2020-12-11",
"Size": "50 MB",
"Version": "vi_1h_2020-12-11",
"Validated_Hr_Total": 0.74,
"Overall_Hr_Total": 1,
"Number_Of_Voice": 62,
},
"vot": {
"Language": "Votic",
"Date": "2020-12-11",
"Size": "7 MB",
"Version": "vot_0.28h_2020-12-11",
"Validated_Hr_Total": 0,
"Overall_Hr_Total": 0.28,
"Number_Of_Voice": 3,
},
"zh-CN": {
"Language": "Chinese (China)",
"Date": "2020-12-11",
"Size": "2 GB",
"Version": "zh-CN_78h_2020-12-11",
"Validated_Hr_Total": 56,
"Overall_Hr_Total": 78,
"Number_Of_Voice": 3501,
},
"zh-HK": {
"Language": "Chinese (Hong Kong)",
"Date": "2020-12-11",
"Size": "3 GB",
"Version": "zh-HK_100h_2020-12-11",
"Validated_Hr_Total": 50,
"Overall_Hr_Total": 100,
"Number_Of_Voice": 2536,
},
"zh-TW": {
"Language": "Chinese (Taiwan)",
"Date": "2020-12-11",
"Size": "2 GB",
"Version": "zh-TW_78h_2020-12-11",
"Validated_Hr_Total": 55,
"Overall_Hr_Total": 78,
"Number_Of_Voice": 1444,
},
}
class CommonVoiceConfig(datasets.BuilderConfig):
"""BuilderConfig for CommonVoice."""
def __init__(self, name, sub_version, **kwargs):
"""
Args:
data_dir: `string`, the path to the folder containing the files in the
downloaded .tar
citation: `string`, citation for the data set
url: `string`, url for information about the data set
**kwargs: keyword arguments forwarded to super.
"""
self.sub_version = sub_version
self.language = kwargs.pop("language", None)
self.date_of_snapshot = kwargs.pop("date", None)
self.size = kwargs.pop("size", None)
self.validated_hr_total = kwargs.pop("val_hrs", None)
self.total_hr_total = kwargs.pop("total_hrs", None)
self.num_of_voice = kwargs.pop("num_of_voice", None)
description = f"Common Voice speech to text dataset in {self.language} version {self.sub_version} of {self.date_of_snapshot}. The dataset comprises {self.validated_hr_total} of validated transcribed speech data from {self.num_of_voice} speakers. The dataset has a size of {self.size}"
super(CommonVoiceConfig, self).__init__(
name=name, version=datasets.Version("6.1.0", ""), description=description, **kwargs
)
class CommonVoice(datasets.GeneratorBasedBuilder):
DEFAULT_WRITER_BATCH_SIZE = 1000
BUILDER_CONFIGS = [
CommonVoiceConfig(
name=lang_id,
language=_LANGUAGES[lang_id]["Language"],
sub_version=_LANGUAGES[lang_id]["Version"],
date=_LANGUAGES[lang_id]["Date"],
size=_LANGUAGES[lang_id]["Size"],
val_hrs=_LANGUAGES[lang_id]["Validated_Hr_Total"],
total_hrs=_LANGUAGES[lang_id]["Overall_Hr_Total"],
num_of_voice=_LANGUAGES[lang_id]["Number_Of_Voice"],
)
for lang_id in _LANGUAGES.keys()
]
def _info(self):
features = datasets.Features(
{
"client_id": datasets.Value("string"),
"path": datasets.Value("string"),
"audio": datasets.Audio(sampling_rate=48_000),
"sentence": datasets.Value("string"),
"up_votes": datasets.Value("int64"),
"down_votes": datasets.Value("int64"),
"age": datasets.Value("string"),
"gender": datasets.Value("string"),
"accent": datasets.Value("string"),
"locale": datasets.Value("string"),
"segment": datasets.Value("string"),
}
)
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=features,
supervised_keys=None,
homepage=_HOMEPAGE,
license=_LICENSE,
citation=_CITATION,
task_templates=[AutomaticSpeechRecognition(audio_column="audio", transcription_column="sentence")],
)
def _split_generators(self, dl_manager):
"""Returns SplitGenerators."""
# Download the TAR archive that contains the audio files:
archive_path = dl_manager.download(_DATA_URL.format(self.config.name))
# First we locate the data using the path within the archive:
path_to_data = "/".join(["cv-corpus-6.1-2020-12-11", self.config.name])
path_to_clips = "/".join([path_to_data, "clips"])
metadata_filepaths = {
split: "/".join([path_to_data, f"{split}.tsv"])
for split in ["train", "test", "dev", "other", "validated", "invalidated"]
}
# (Optional) In non-streaming mode, we can extract the archive locally to have actual local audio files:
local_extracted_archive = dl_manager.extract(archive_path) if not dl_manager.is_streaming else None
# To access the audio data from the TAR archives using the download manager,
# we have to use the dl_manager.iter_archive method.
#
# This is because dl_manager.download_and_extract
# doesn't work to stream TAR archives in streaming mode.
# (we have to stream the files of a TAR archive one by one)
#
# The iter_archive method returns an iterable of (path_within_archive, file_obj) for every
# file in the TAR archive.
return [
datasets.SplitGenerator(
name=datasets.Split.TRAIN,
gen_kwargs={
"local_extracted_archive": local_extracted_archive,
"archive_iterator": dl_manager.iter_archive(
archive_path
), # use iter_archive here to access the files in the TAR archives
"metadata_filepath": metadata_filepaths["train"],
"path_to_clips": path_to_clips,
},
),
datasets.SplitGenerator(
name=datasets.Split.TEST,
gen_kwargs={
"local_extracted_archive": local_extracted_archive,
"archive_iterator": dl_manager.iter_archive(
archive_path
), # use iter_archive here to access the files in the TAR archives
"metadata_filepath": metadata_filepaths["test"],
"path_to_clips": path_to_clips,
},
),
datasets.SplitGenerator(
name=datasets.Split.VALIDATION,
gen_kwargs={
"local_extracted_archive": local_extracted_archive,
"archive_iterator": dl_manager.iter_archive(
archive_path
), # use iter_archive here to access the files in the TAR archives
"metadata_filepath": metadata_filepaths["dev"],
"path_to_clips": path_to_clips,
},
),
datasets.SplitGenerator(
name="other",
gen_kwargs={
"local_extracted_archive": local_extracted_archive,
"archive_iterator": dl_manager.iter_archive(
archive_path
), # use iter_archive here to access the files in the TAR archives
"metadata_filepath": metadata_filepaths["other"],
"path_to_clips": path_to_clips,
},
),
datasets.SplitGenerator(
name="validated",
gen_kwargs={
"local_extracted_archive": local_extracted_archive,
"archive_iterator": dl_manager.iter_archive(
archive_path
), # use iter_archive here to access the files in the TAR archives
"metadata_filepath": metadata_filepaths["validated"],
"path_to_clips": path_to_clips,
},
),
datasets.SplitGenerator(
name="invalidated",
gen_kwargs={
"local_extracted_archive": local_extracted_archive,
"archive_iterator": dl_manager.iter_archive(
archive_path
), # use iter_archive here to access the files in the TAR archives
"metadata_filepath": metadata_filepaths["invalidated"],
"path_to_clips": path_to_clips,
},
),
]
def _generate_examples(self, local_extracted_archive, archive_iterator, metadata_filepath, path_to_clips):
"""Yields examples."""
data_fields = list(self._info().features.keys())
# audio is not a header of the csv files
data_fields.remove("audio")
path_idx = data_fields.index("path")
all_field_values = {}
metadata_found = False
# Here we iterate over all the files within the TAR archive:
for path, f in archive_iterator:
# Parse the metadata CSV file
if path == metadata_filepath:
metadata_found = True
lines = f.readlines()
headline = lines[0].decode("utf-8")
column_names = headline.strip().split("\t")
assert (
column_names == data_fields
), f"The file should have {data_fields} as column names, but has {column_names}"
for line in lines[1:]:
field_values = line.decode("utf-8").strip().split("\t")
# set full path for mp3 audio file
audio_path = "/".join([path_to_clips, field_values[path_idx]])
all_field_values[audio_path] = field_values
# Else, read the audio file and yield an example
elif path.startswith(path_to_clips):
assert metadata_found, "Found audio clips before the metadata TSV file."
if not all_field_values:
break
if path in all_field_values:
# retrieve the metadata corresponding to this audio file
field_values = all_field_values[path]
# if data is incomplete, fill with empty values
if len(field_values) < len(data_fields):
field_values += (len(data_fields) - len(field_values)) * ["''"]
result = {key: value for key, value in zip(data_fields, field_values)}
# set audio feature
path = os.path.join(local_extracted_archive, path) if local_extracted_archive else path
result["audio"] = {"path": path, "bytes": f.read()}
# set path to None if the audio file doesn't exist locally (i.e. in streaming mode)
result["path"] = path if local_extracted_archive else None
yield path, result