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The LibriTTS Corpus with Forced Alignments dataset is a speech dataset for automatic speech recognition (ASR) and text‑to‑speech (TTS) tasks. It includes audio files, corresponding transcripts, phonemes, and their durations. The dataset provides pre‑processed alignment information so users do not need to run the Montreal Forced Aligner locally. A data collator is also provided to create training batches. The dataset is divided into several subsets (train, dev, test, etc.) corresponding to different subsets of LibriSpeech.

--- 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 - text-to-speech - text-to-audio 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 around 44-hours of 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 - `automatic-speech-recognition`, `speaker-identification`: The dataset can be used to train a model for Automatic Speech Recognition (ASR). The model is presented with an audio file and asked to transcribe the audio file to written text. The most common evaluation metric is the word error rate (WER). - `text-to-speech`, `text-to-audio`: The dataset can also be used to train a model for Text-To-Speech (TTS). ### 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.