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README.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.

dataset_infos.json

@@ -1 +0,0 @@
-{"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}}

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vctk.py

@@ -1,133 +0,0 @@
-# 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