metadata
language:
- de
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- de
- robust-speech-event
datasets:
- mozilla-foundation/common_voice_8_0
model-index:
- name: XLS-R-1B - German
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 8
type: mozilla-foundation/common_voice_8_0
args: de
metrics:
- name: Test WER
type: wer
value: 10.95
- name: Test CER
type: cer
value: 2.72
- name: Test WER (+LM)
type: wer
value: 8.13
- name: Test CER (+LM)
type: cer
value: 2.18
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Dev Data
type: speech-recognition-community-v2/dev_data
args: de
metrics:
- name: Test WER
type: wer
value: 22.68
- name: Test CER
type: cer
value: 9.17
- name: Test WER (+LM)
type: wer
value: 17.07
- name: Test CER (+LM)
type: cer
value: 8.45
XLS-R-1B-GERMAN
Fine-tuned facebook/wav2vec2-xls-r-1b on German using the Common Voice 8. When using this model, make sure that your speech input is sampled at 16kHz.
This model has been fine-tuned thanks to the GPU credits generously given by the OVHcloud :)
The script used for training can be found here: https://github.com/jonatasgrosman/wav2vec2-sprint
Evaluation Commands
- To evaluate on
mozilla-foundation/common_voice_8_0
with splittest
python eval.py --model_id jonatasgrosman/wav2vec2-xls-r-1b-german --dataset mozilla-foundation/common_voice_8_0 --config de --split test
- To evaluate on
speech-recognition-community-v2/dev_data
python eval.py --model_id jonatasgrosman/wav2vec2-xls-r-1b-german --dataset speech-recognition-community-v2/dev_data --config de --split validation --chunk_length_s 5.0 --stride_length_s 1.0