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README-en.md

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+---
+annotations_creators:
+- expert-generated
+language_creators:
+- crowdsourced
+language:
+- en
+license:
+- cc-by-4.0
+multilinguality:
+- monolingual
+pretty_name: VCTK
+size_categories:
+- 10K<n<100K
+source_datasets:
+- original
+task_categories:
+- automatic-speech-recognition
+task_ids: []
+paperswithcode_id: vctk
+train-eval-index:
+- config: main
+  task: automatic-speech-recognition
+  task_id: speech_recognition
+  splits:
+    train_split: train
+  col_mapping:
+    file: path
+    text: text
+  metrics:
+  - type: wer
+    name: WER
+  - type: cer
+    name: CER
+dataset_info:
+  features:
+  - name: speaker_id
+    dtype: string
+  - name: audio
+    dtype:
+      audio:
+        sampling_rate: 48000
+  - name: file
+    dtype: string
+  - name: text
+    dtype: string
+  - name: text_id
+    dtype: string
+  - name: age
+    dtype: string
+  - name: gender
+    dtype: string
+  - name: accent
+    dtype: string
+  - name: region
+    dtype: string
+  - name: comment
+    dtype: string
+  config_name: main
+  splits:
+  - name: train
+    num_bytes: 40103111
+    num_examples: 88156
+  download_size: 11747302977
+  dataset_size: 40103111
+---
+
+# Dataset Card for VCTK
+
+## Table of Contents
+- [Dataset Description](#dataset-description)
+  - [Dataset Summary](#dataset-summary)
+  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
+  - [Languages](#languages)
+- [Dataset Structure](#dataset-structure)
+  - [Data Instances](#data-instances)
+  - [Data Fields](#data-fields)
+  - [Data Splits](#data-splits)
+- [Dataset Creation](#dataset-creation)
+  - [Curation Rationale](#curation-rationale)
+  - [Source Data](#source-data)
+  - [Annotations](#annotations)
+  - [Personal and Sensitive Information](#personal-and-sensitive-information)
+- [Considerations for Using the Data](#considerations-for-using-the-data)
+  - [Social Impact of Dataset](#social-impact-of-dataset)
+  - [Discussion of Biases](#discussion-of-biases)
+  - [Other Known Limitations](#other-known-limitations)
+- [Additional Information](#additional-information)
+  - [Dataset Curators](#dataset-curators)
+  - [Licensing Information](#licensing-information)
+  - [Citation Information](#citation-information)
+  - [Contributions](#contributions)
+
+## Dataset Description
+
+- **Homepage:** [Edinburg DataShare](https://doi.org/10.7488/ds/2645)
+- **Repository:**
+- **Paper:**
+- **Leaderboard:**
+- **Point of Contact:**
+
+### Dataset Summary
+
+This CSTR VCTK Corpus includes speech data uttered by 110 English speakers with various accents. Each speaker reads out about 400 sentences, which were selected from a newspaper, the rainbow passage and an elicitation paragraph used for the speech accent archive.
+
+### Supported Tasks and Leaderboards
+
+[More Information Needed]
+
+### Languages
+
+[More Information Needed]
+
+## Dataset Structure
+
+### Data Instances
+
+A data point comprises the path to the audio file, called `file` and its transcription, called `text`.
+
+```
+{
+  'speaker_id': 'p225',
+  'text_id': '001',
+  'text': 'Please call Stella.',
+  'age': '23',
+  'gender': 'F',
+  'accent': 'English',
+  'region': 'Southern England',
+  'file': '/datasets/downloads/extracted/8ed7dad05dfffdb552a3699777442af8e8ed11e656feb277f35bf9aea448f49e/wav48_silence_trimmed/p225/p225_001_mic1.flac',
+  'audio':
+    {
+      'path': '/datasets/downloads/extracted/8ed7dad05dfffdb552a3699777442af8e8ed11e656feb277f35bf9aea448f49e/wav48_silence_trimmed/p225/p225_001_mic1.flac',
+      'array': array([0.00485229, 0.00689697, 0.00619507, ..., 0.00811768, 0.00836182, 0.00854492], dtype=float32),
+      'sampling_rate': 48000
+    },
+  'comment': ''
+}
+```
+
+Each audio file is a single-channel FLAC with a sample rate of 48000 Hz.
+
+### Data Fields
+
+Each row consists of the following fields:
+
+- `speaker_id`: Speaker ID
+- `audio`: Audio recording
+- `file`: Path to audio file
+- `text`: Text transcription of corresponding audio
+- `text_id`: Text ID
+- `age`: Speaker's age
+- `gender`: Speaker's gender
+- `accent`: Speaker's accent
+- `region`: Speaker's region, if annotation exists
+- `comment`: Miscellaneous comments, if any
+
+### Data Splits
+
+The dataset has no predefined splits.
+
+## Dataset Creation
+
+### Curation Rationale
+
+[More Information Needed]
+
+### Source Data
+
+#### Initial Data Collection and Normalization
+
+[More Information Needed]
+
+#### Who are the source language producers?
+
+[More Information Needed]
+
+### Annotations
+
+#### Annotation process
+
+[More Information Needed]
+
+#### Who are the annotators?
+
+[More Information Needed]
+
+### Personal and Sensitive Information
+
+The dataset consists of people who have donated their voice online.  You agree to not attempt to determine the identity of speakers in this dataset.
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[More Information Needed]
+
+### Discussion of Biases
+
+[More Information Needed]
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed]
+
+### Licensing Information
+
+Public Domain, Creative Commons Attribution 4.0 International Public License ([CC-BY-4.0](https://creativecommons.org/licenses/by/4.0/legalcode))
+
+### Citation Information
+
+```bibtex
+@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
+}
+```
+
+### Contributions
+
+Thanks to [@jaketae](https://github.com/jaketae) for adding this dataset.

README.md

@@ -0,0 +1,3 @@
+
+copy from https://huggingface.co/datasets/vctk
+and support set data_files

dataset_infos.json

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+{"main": {"description": "", "citation": "@inproceedings{Veaux2017CSTRVC,\n\ttitle        = {CSTR VCTK Corpus: English Multi-speaker Corpus for CSTR Voice Cloning Toolkit},\n\tauthor       = {Christophe Veaux and Junichi Yamagishi and Kirsten MacDonald},\n\tyear         = 2017\n}\n", "homepage": "https://datashare.ed.ac.uk/handle/10283/3443", "license": "", "features": {"speaker_id": {"dtype": "string", "id": null, "_type": "Value"}, "audio": {"sampling_rate": 48000, "mono": true, "_storage_dtype": "string", "id": null, "_type": "Audio"}, "file": {"dtype": "string", "id": null, "_type": "Value"}, "text": {"dtype": "string", "id": null, "_type": "Value"}, "text_id": {"dtype": "string", "id": null, "_type": "Value"}, "age": {"dtype": "string", "id": null, "_type": "Value"}, "gender": {"dtype": "string", "id": null, "_type": "Value"}, "accent": {"dtype": "string", "id": null, "_type": "Value"}, "region": {"dtype": "string", "id": null, "_type": "Value"}, "comment": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": {"input": "file", "output": "text"}, "task_templates": [{"task": "automatic-speech-recognition", "audio_column": "audio", "transcription_column": "text"}], "builder_name": "vctk", "config_name": "main", "version": {"version_str": "0.9.2", "description": null, "major": 0, "minor": 9, "patch": 2}, "splits": {"train": {"name": "train", "num_bytes": 40103111, "num_examples": 88156, "dataset_name": "vctk"}}, "download_checksums": {"https://datashare.is.ed.ac.uk/bitstream/handle/10283/3443/VCTK-Corpus-0.92.zip": {"num_bytes": 11747302977, "checksum": "f96258be9fdc2cbff6559541aae7ea4f59df3fcaf5cf963aae5ca647357e359c"}}, "download_size": 11747302977, "post_processing_size": null, "dataset_size": 40103111, "size_in_bytes": 11787406088}}

vctk.py

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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):
+        if self.config.data_files:
+            root_path = self.config.data_files
+        else:
+            root_path = _DL_URL
+        root_path = dl_manager.download_and_extract(root_path)
+
+        if isinstance(root_path,dict):
+            root_path = root_path['train'][0]
+
+        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