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---
license: other
language: "de"
thumbnail:
tags:
- automatic-speech-recognition
- CTC
- Attention
- pytorch
- speechbrain
metrics:
- wer
---
# German ASR
This model is trained on the Mozilla Common Voice 6.1, the Spoken Wikipedia Corpus and the m-ailabs corpus.
- https://nats.gitlab.io/swc/
- https://commonvoice.mozilla.org/de/datasets
- https://www.caito.de/2019/01/03/the-m-ailabs-speech-dataset/
We do not provide a language model.
# Performance
This model has a WER of 7.24%.
# Model application
## Install SpeechBrain
First of all, please install SpeechBrain with the following command:
```
pip install speechbrain
```
Please notice that we encourage you to read our tutorials and learn more about
[SpeechBrain](https://speechbrain.github.io).
## Using the model
```
from speechbrain.pretrained import EncoderDecoderASR
asr_model = EncoderDecoderASR.from_hparams(source="jfreiwa/asr-crdnn-german", savedir="pretrained_models/asr-crdnn-german")
asr_model.transcribe_file("jfreiwa/asr-crdnn-german/example-de.wav")
```
## Inference on GPU
To perform inference on the GPU, add `run_opts={"device":"cuda"}` when calling the `from_hparams` method.
# Limitations
We do not provide any warranty on the performance achieved by this model when used on other datasets.
# **About SpeechBrain**
- Website: https://speechbrain.github.io/
- Code: https://github.com/speechbrain/speechbrain/
- HuggingFace: https://huggingface.co/speechbrain/
# **Citing SpeechBrain**
Please, cite SpeechBrain if you use it for your research or business.
```bibtex
@misc{speechbrain,
title={{SpeechBrain}: A General-Purpose Speech Toolkit},
author={Mirco Ravanelli and Titouan Parcollet and Peter Plantinga and Aku Rouhe and Samuele Cornell and Loren Lugosch and Cem Subakan and Nauman Dawalatabad and Abdelwahab Heba and Jianyuan Zhong and Ju-Chieh Chou and Sung-Lin Yeh and Szu-Wei Fu and Chien-Feng Liao and Elena Rastorgueva and François Grondin and William Aris and Hwidong Na and Yan Gao and Renato De Mori and Yoshua Bengio},
year={2021},
eprint={2106.04624},
archivePrefix={arXiv},
primaryClass={eess.AS},
note={arXiv:2106.04624}
}
```
# **Citing our paper**
We will provide a bibtex-entry soon.
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