---
dataset_info:
  features:
  - name: audio
    dtype: audio
  - name: transcription
    dtype: string
  splits:
  - name: train
    num_bytes: 109304535928.432
    num_examples: 90244
  - name: validation
    num_bytes: 1051506219.236
    num_examples: 1013
  - name: test
    num_bytes: 1226193261.48
    num_examples: 1020
  download_size: 93176985982
  dataset_size: 111582235409.148
license: cc-by-nc-4.0
task_categories:
- automatic-speech-recognition
- audio-classification
tags:
- automatic-speech-recognition
- audio-classification
- Portuguese
- ASR
language:
- pt
pretty_name: mTEDx PTBR
---

# Multilingual TEDx (Portuguese speech and transcripts)

**NOTE:** This dataset contains only the Portuguese portion of the mTEDx dataset, already processed and segmented into parts.

**Multilingual TEDx (mTEDx)** is a multilingual speech recognition and translation corpus to facilitate the training of ASR and SLT models in additional languages.

The corpus comprises audio recordings and transcripts from [TEDx Talks](https://www.ted.com/watch/tedx-talks) in 8 languages (Spanish, French, Portuguese, Italian, Russian, Greek, Arabic, German) with translations into up to 5 languages (English, Spanish, French, Portguese, Italian).
The audio recordings are automatically aligned at the sentence level with their manual transcriptions and translations.
Each .tgz file contains two directories: data and docs. docs contains a README detailing the files provided in data and their structure.
Test sets for all [IWSLT 2021](https://iwslt.org/2021/multilingual) language pairs can be found in mtedx_iwslt2021.tgz.
For more information on the dataset please see the [dataset paper](https://arxiv.org/abs/2102.01757). 

Contact: Elizabeth Salesky, Matthew Wiesner. [esalesky@jhu.edu, wiesner@jhu.edu](mailto:esalesky@jhu.edu;wiesner@jhu.edu;)

Citation: If you use the Multilingual TEDx corpus in your work, please cite the dataset paper:

```latex
@inproceedings{salesky2021mtedx,
  title={Multilingual TEDx Corpus for Speech Recognition and Translation},
  author={Elizabeth Salesky and Matthew Wiesner and Jacob Bremerman and Roldano Cattoni and Matteo Negri and Marco Turchi and Douglas W. Oard and Matt Post},
  booktitle={Proceedings of Interspeech},
  year={2021},
}
```