The Multilingual TEDx Corpus for Speech Recognition and Translation

By Elizabeth Salesky, Matthew Wiesner, Jacob Bremerman, Roldano Cattoni, Matteo Negri, Marco Turchi, Douglas W. Oard, Matt Post. 2021

154 citations recorded by the source corpus.

We present the Multilingual TEDx corpus, built to support speech recognition (ASR) and speech translation (ST) research across many non-English source languages. The corpus is a collection of audio recordings from TEDx talks in 8 source languages. We segment transcripts into sentences and align them to the source-language audio and target-language translations. The corpus is released along with open-sourced code enabling extension to new talks and languages as they become available. Our corpus creation methodology can be applied to more languages than previous work, and creates multi-way parallel evaluation sets. We provide baselines in multiple ASR and ST settings, including multilingual models to improve translation performance for low-resource language pairs.

Subfields: Artificial Intelligence, Machine Translation, Speech & Audio

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Yu Zhang
2. Graham Neubig
3. Ankur Bapna
4. Orhan Firat
5. Sebastian Ruder
6. Alexis Conneau
7. Tie-Yan Liu
8. Tao Qin

In Machine Translation

1. Ye Jia
2. Ankur Bapna
3. Colin Cherry
4. J. Clark
5. Melvin Johnson
6. Rong Ye
7. Yu Zhang
8. Michael Auli

In Speech & Audio

1. Yu Zhang
2. Ye Jia
3. Alexis Conneau
4. Ankur Bapna
5. Wei Ping
6. Boris Ginsburg
7. Tom Ko
8. Bryan Catanzaro

Citations in the corpus

• FLEURS: FEW-Shot Learning Evaluation of Universal Representations of Speech (2022, background): “4k hrs TED talks Spontaneous Yes Yes No mTEDx [20] 9 1k hrs TED talks Spontaneous Yes Yes No CVSS [21] 22 1.”
• BigVGAN: A Universal Neural Vocoder with Large-Scale Training (2022, background): “• The Multilingual TEDx Corpus [48]: contains a collection of TEDx talks in Spanish, French, Italian, and Portuguese.”
• GigaST: A 10, 000-hour Pseudo Speech Translation Corpus (2022, background): “1https://github.com/bytedance/neurst/ such as MuST-C [8] and TEDx [9].”
• XTREME-S: Evaluating Cross-lingual Speech Representations (2022, background): “Europarl-ST [22], Must-C [23] and mTEDX [24] also provide common evaluation of speech translation.”