CVSS: A Massively Multilingual Speech-to-Speech Translation Corpus

Related tags

Text Data & NLPcvss
Overview

CVSS: A Massively Multilingual Speech-to-Speech Translation Corpus

License: CC BY 4.0

CVSS is a massively multilingual-to-English speech-to-speech translation corpus, covering sentence-level parallel speech-to-speech translation pairs from 21 languages into English. CVSS is derived from the Common Voice speech corpus and the CoVoST 2 speech-to-text translation corpus. The translation speech in CVSS is synthesized with two state-of-the-art TTS models trained on the LibriTTS corpus.

CVSS includes two versions of spoken translation for all the 21 x-en language pairs from CoVoST 2, with each version providing unique values:

  • CVSS-C: All the translation speeches are in a single canonical speaker's voice. Despite being synthetic, these speeches are of very high naturalness and cleanness, as well as having consistent speaking style. These properties ease the modelling of the target speech and enable models to produce high quality translation speech suitable for user-facing applications.

  • CVSS-T: The translation speeches are in voices transferred from the corresponding source speeches. Each translation pair has similar voices on the two sides despite of being in different languages, making this dataset suitable for building models that preserve speakers' voices when translate speech into different languages.

In together with the source speeches originated from Common Voice, they make two multilingual speech-to-speech tranlsation datasets each with about 1,900 hours of speech.

In addition to translation speech, CVSS also provides normalized translation text matching the pronunciation in the translation speech (e.g. on numbers, currencies, acronyms, etc.), which can be use for both model training as well as standalizing evaluation.

Please check out our paper for the detailed description of this corpus, as well as the baseline models we trained on both datasets.

Getting the data

The translation speech and the normalized translation text in CVSS can be downloaded from the links in the following table:

Source language Code CVSS-C CVSS-T
Arabic ar link link
Catalan ca link link
Welsh cy link link
German de link link
Estonian et link link
Spanish es link link
Persian fa link link
French fr link link
Indonesian id link link
Italian it link link
Japanese ja link link
Latvian lv link link
Mongolian mn link link
Dutch nl link link
Portuguese pt link link
Russian ru link link
Slovenian sl link link
Swedish sv link link
Tamil ta link link
Turkish tr link link
Chinese zh link link

Each tar.gz file in the links above includes train, dev and test directories containing audio clips as the translation speech, as well as train.tsv, dev.tsv and test.tsv files containing the normalized translation text. The normalized translation text files included in CVSS-C and CVSS-T are identical.

These translation audio clips and translation texts are to be paired with the Common Voice release version 4 (required) based on the audio file names. If you need the original translation text without the normalization, they are provided by CoVoST 2.

License

CVSS is released under the very permissive Creative Commons Attribution 4.0 International (CC BY 4.0) license.

Citation

Please cite this paper when referencing the CVSS corpus:

@misc{jia2022cvss,
    title={{CVSS} Corpus and Massively Multilingual Speech-to-Speech Translation},
    author={Jia, Ye and Tadmor Ramanovich, Michelle and Wang, Quan and Zen, Heiga},
    eprint={2201.03713},
    archivePrefix={arXiv},
    year={2022}
}
Owner
Google Research Datasets
Datasets released by Google Research
Google Research Datasets
Stack based programming language that compiles to x86_64 assembly or can alternatively be interpreted in Python

lang lang is a simple stack based programming language written in Python. It can

Christoffer Aakre 1 May 30, 2022
precise iris segmentation

PI-DECODER Introduction PI-DECODER, a decoder structure designed for Precise Iris Segmentation and Location. The decoder structure is shown below: Ple

8 Aug 08, 2022
Awesome-NLP-Research (ANLP)

Awesome-NLP-Research (ANLP)

Language, Information, and Learning at Yale 72 Dec 19, 2022
Main repository for the chatbot Bobotinho.

Bobotinho Bot Main repository for the chatbot Bobotinho. ℹ️ Introduction Twitch chatbot with entertainment commands. ‎ 💻 Technologies Concurrent code

Bobotinho 14 Nov 29, 2022
[EMNLP 2021] Mirror-BERT: Converting Pretrained Language Models to universal text encoders without labels.

[EMNLP 2021] Mirror-BERT: Converting Pretrained Language Models to universal text encoders without labels.

Cambridge Language Technology Lab 61 Dec 10, 2022
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations

ALBERT ***************New March 28, 2020 *************** Add a colab tutorial to run fine-tuning for GLUE datasets. ***************New January 7, 2020

Google Research 3k Dec 26, 2022
This is the main repository of open-sourced speech technology by Huawei Noah's Ark Lab.

Speech-Backbones This is the main repository of open-sourced speech technology by Huawei Noah's Ark Lab. Grad-TTS Official implementation of the Grad-

HUAWEI Noah's Ark Lab 295 Jan 07, 2023
customer care chatbot made with Rasa Open Source.

Customer Care Bot Customer care bot for ecomm company which can solve faq and chitchat with users, can contact directly to team. 🛠 Features Basic E-c

Dishant Gandhi 23 Oct 27, 2022
To be a next-generation DL-based phenotype prediction from genome mutations.

Sequence -----------+-- 3D_structure -- 3D_module --+ +-- ? | |

Eric Alcaide 18 Jan 11, 2022
Search for documents in a domain through Google. The objective is to extract metadata

MetaFinder - Metadata search through Google _____ __ ___________ .__ .___ / \

Josué Encinar 85 Dec 16, 2022
Code for the Findings of NAACL 2022(Long Paper): AdapterBias: Parameter-efficient Token-dependent Representation Shift for Adapters in NLP Tasks

AdapterBias: Parameter-efficient Token-dependent Representation Shift for Adapters in NLP Tasks arXiv link: upcoming To be published in Findings of NA

Allen 16 Nov 12, 2022
Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis (SV2TTS)

This repository is an implementation of Transfer Learning from Speaker Verification to Multispeaker Text-To-Speech Synthesis (SV2TTS) with a vocoder that works in real-time. Feel free to check my the

Corentin Jemine 38.5k Jan 03, 2023
Awesome Treasure of Transformers Models Collection

💁 Awesome Treasure of Transformers Models for Natural Language processing contains papers, videos, blogs, official repo along with colab Notebooks. 🛫☑️

Ashish Patel 577 Jan 07, 2023
Generate custom detailed survey paper with topic clustered sections and proper citations, from just a single query in just under 30 mins !!

Auto-Research A no-code utility to generate a detailed well-cited survey with topic clustered sections (draft paper format) and other interesting arti

Sidharth Pal 20 Dec 14, 2022
Bidirectional Variational Inference for Non-Autoregressive Text-to-Speech (BVAE-TTS)

Bidirectional Variational Inference for Non-Autoregressive Text-to-Speech (BVAE-TTS) Yoonhyung Lee, Joongbo Shin, Kyomin Jung Abstract: Although early

LEE YOON HYUNG 147 Dec 05, 2022
Use Google's BERT for named entity recognition (CoNLL-2003 as the dataset).

For better performance, you can try NLPGNN, see NLPGNN for more details. BERT-NER Version 2 Use Google's BERT for named entity recognition (CoNLL-2003

Kaiyinzhou 1.2k Dec 26, 2022
Practical Natural Language Processing Tools for Humans is build on the top of Senna Natural Language Processing (NLP)

Practical Natural Language Processing Tools for Humans is build on the top of Senna Natural Language Processing (NLP) predictions: part-of-speech (POS) tags, chunking (CHK), name entity recognition (

jawahar 20 Apr 30, 2022
LOT: A Benchmark for Evaluating Chinese Long Text Understanding and Generation

LOT: A Benchmark for Evaluating Chinese Long Text Understanding and Generation Tasks | Datasets | LongLM | Baselines | Paper Introduction LOT is a ben

46 Dec 28, 2022
CPC-big and k-means clustering for zero-resource speech processing

The CPC-big model and k-means checkpoints used in Analyzing Speaker Information in Self-Supervised Models to Improve Zero-Resource Speech Processing.

Benjamin van Niekerk 5 Nov 23, 2022
Explore different way to mix speech model(wav2vec2, hubert) and nlp model(BART,T5,GPT) together

SpeechMix Explore different way to mix speech model(wav2vec2, hubert) and nlp model(BART,T5,GPT) together. Introduction For the same input: from datas

Eric Lam 31 Nov 07, 2022