Datasets:
Languages:
English
Multilinguality:
monolingual
Size Categories:
10K<n<100K
Language Creators:
crowdsourced
Annotations Creators:
expert-generated
Source Datasets:
original
License:
File size: 5,314 Bytes
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# coding=utf-8
# Copyright 2021 The TensorFlow Datasets Authors and the HuggingFace Datasets Authors.
#
# 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.
# Lint as: python3
"""VCTK dataset."""
import os
import re
import datasets
from datasets.tasks import AutomaticSpeechRecognition
_CITATION = """\
@inproceedings{Veaux2017CSTRVC,
title = {CSTR VCTK Corpus: English Multi-speaker Corpus for CSTR Voice Cloning Toolkit},
author = {Christophe Veaux and Junichi Yamagishi and Kirsten MacDonald},
year = 2017
}
"""
_DESCRIPTION = """\
The CSTR VCTK Corpus includes speech data uttered by 110 English speakers with various accents.
"""
_URL = "https://datashare.ed.ac.uk/handle/10283/3443"
_DL_URL = "https://datashare.is.ed.ac.uk/bitstream/handle/10283/3443/VCTK-Corpus-0.92.zip"
class VCTK(datasets.GeneratorBasedBuilder):
"""VCTK dataset."""
VERSION = datasets.Version("0.9.2")
BUILDER_CONFIGS = [
datasets.BuilderConfig(name="main", version=VERSION, description="VCTK dataset"),
]
def _info(self):
return datasets.DatasetInfo(
description=_DESCRIPTION,
features=datasets.Features(
{
"speaker_id": datasets.Value("string"),
"audio": datasets.features.Audio(sampling_rate=48_000),
"file": datasets.Value("string"),
"text": datasets.Value("string"),
"text_id": datasets.Value("string"),
"age": datasets.Value("string"),
"gender": datasets.Value("string"),
"accent": datasets.Value("string"),
"region": datasets.Value("string"),
"comment": datasets.Value("string"),
}
),
supervised_keys=("file", "text"),
homepage=_URL,
citation=_CITATION,
task_templates=[AutomaticSpeechRecognition(audio_column="audio", transcription_column="text")],
)
def _split_generators(self, dl_manager):
root_path = dl_manager.download_and_extract(_DL_URL)
return [
datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"root_path": root_path}),
]
def _generate_examples(self, root_path):
"""Generate examples from the VCTK corpus root path."""
meta_path = os.path.join(root_path, "speaker-info.txt")
txt_root = os.path.join(root_path, "txt")
wav_root = os.path.join(root_path, "wav48_silence_trimmed")
# NOTE: "comment" is handled separately in logic below
fields = ["speaker_id", "age", "gender", "accent", "region"]
key = 0
with open(meta_path, encoding="utf-8") as meta_file:
_ = next(iter(meta_file))
for line in meta_file:
data = {}
line = line.strip()
search = re.search(r"\(.*\)", line)
if search is None:
data["comment"] = ""
else:
start, _ = search.span()
data["comment"] = line[start:]
line = line[:start]
values = line.split()
for i, field in enumerate(fields):
if field == "region":
data[field] = " ".join(values[i:])
else:
data[field] = values[i] if i < len(values) else ""
speaker_id = data["speaker_id"]
speaker_txt_path = os.path.join(txt_root, speaker_id)
speaker_wav_path = os.path.join(wav_root, speaker_id)
# NOTE: p315 does not have text
if not os.path.exists(speaker_txt_path):
continue
for txt_file in sorted(os.listdir(speaker_txt_path)):
filename, _ = os.path.splitext(txt_file)
_, text_id = filename.split("_")
for i in [1, 2]:
wav_file = os.path.join(speaker_wav_path, f"{filename}_mic{i}.flac")
# NOTE: p280 does not have mic2 files
if not os.path.exists(wav_file):
continue
with open(os.path.join(speaker_txt_path, txt_file), encoding="utf-8") as text_file:
text = text_file.readline().strip()
more_data = {
"file": wav_file,
"audio": wav_file,
"text": text,
"text_id": text_id,
}
yield key, {**data, **more_data}
key += 1
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