MustC Speech Translation
That's awesome! Actually, I just noticed that this dataset might become a bit too big!

MuST-C is the main dataset used for IWSLT19 and should probably be added as a standalone dataset. Would you be interested also in adding `datasets/MuST-C` instead?

Description: 
_MuST-C is a multilingual speech translation corpus whose size and quality facilitates the training of end-to-end systems for speech translation from English into several languages. For each target language, MuST-C comprises several hundred hours of audio recordings from English TED Talks, which are automatically aligned at the sentence level with their manual transcriptions and translations._

Paper: https://www.aclweb.org/anthology/N19-1202.pdf

Dataset: https://ict.fbk.eu/must-c/ (One needs to fill out a short from to download the data, but it's very easy).

It would be awesome if you're interested in adding this datates. I'm very happy to guide you through the PR! I think the easiest way to start would probably be to read [this README on how to add a dataset](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md) and open a PR. Think you can copy & paste some code from:

- Librispeech_asr: https://github.com/huggingface/datasets/blob/master/datasets/librispeech_asr/librispeech_asr.py
- Flores Translation: https://github.com/huggingface/datasets/blob/master/datasets/flores/flores.py

Think all the rest can be handled on the PR :-) 
## Adding a Dataset
- **Name:** *IWSLT19*
- **Description:** *The Speech Translation Task addresses the translation of English audio into German and Portuguese text.*
- **Hompage:** *https://sites.google.com/view/iwslt-evaluation-2019/speech-translation*
- **Data:** *https://sites.google.com/view/iwslt-evaluation-2019/speech-translation* - all data under "Allowed Training Data" and "Development and Evalutaion Data for TED/How2"
- **Motivation:** Important speech dataset

If interested in tackling this issue, feel free to tag @patrickvonplaten

Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).

MustC Speech Translation 
 ## Adding a Dataset
- **Name:** *IWSLT19*
- **Description:** *The Speech Translation Task addresses the translation of English audio into German and Portuguese text.*
- **Hompage:** *https://sites.google.com/view/iwslt-evaluation-2019/speech-translation*
- **Data:** *https://sites.google.com/view/iwslt-evaluation-2019/speech-translation* - all data under "Allowed Training Data" and "Development and Evalutaion Data for TED/How2"
- **Motivation:** Important speech dataset

If interested in tackling this issue, feel free to tag @patrickvonplaten

Instructions to add a new dataset can be found [here](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md).
 
 That's awesome! Actually, I just noticed that this dataset might become a bit too big!

MuST-C is the main dataset used for IWSLT19 and should probably be added as a standalone dataset. Would you be interested also in adding `datasets/MuST-C` instead?

Description: 
_MuST-C is a multilingual speech translation corpus whose size and quality facilitates the training of end-to-end systems for speech translation from English into several languages. For each target language, MuST-C comprises several hundred hours of audio recordings from English TED Talks, which are automatically aligned at the sentence level with their manual transcriptions and translations._

Paper: https://www.aclweb.org/anthology/N19-1202.pdf

Dataset: https://ict.fbk.eu/must-c/ (One needs to fill out a short from to download the data, but it's very easy).

It would be awesome if you're interested in adding this datates. I'm very happy to guide you through the PR! I think the easiest way to start would probably be to read [this README on how to add a dataset](https://github.com/huggingface/datasets/blob/master/ADD_NEW_DATASET.md) and open a PR. Think you can copy & paste some code from:

- Librispeech_asr: https://github.com/huggingface/datasets/blob/master/datasets/librispeech_asr/librispeech_asr.py
- Flores Translation: https://github.com/huggingface/datasets/blob/master/datasets/flores/flores.py

Think all the rest can be handled on the PR :-) 