metadata
language:
- et
license: apache-2.0
metrics:
- wer
model-index:
- name: conformer-ctc et
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: ERR2020
args: et
metrics:
- name: Wer
type: wer
value: 12.1
conformer-ctc et
Icefall conformer-ctc3 based recipe (https://github.com/k2-fsa/icefall/tree/master/egs/librispeech/ASR/conformer_ctc3) trained Estonian ASR model using ERR2020 dataset
- WER on ERR2020: 12.1
- WER on mozilla commonvoice_11: 24.5
For usage:
- clone this repo (
git clone https://huggingface.co/rristo/icefall_conformer_ctc3_et
) - go to repo (
cd icefall_conformer_ctc3_et
) - build docker image for needed libraries (
build.sh
orbuild.bat
) - run docker container (
run.sh
orrun.sh
). This mounts current directory - run notebook
err2020/conformer_ctc3_usage.ipynb
for example usage- currently expects audio to be in .wav format
Model description
ASR model for Estonian, uses Estonian Public Broadcasting data ERR2020 data (around 230 hours of audio)
Intended uses & limitations
Pretty much a toy model, trained on limited amount of data. Might not work well on data out of domain (especially spontaneous/noisy data).
Training and evaluation data
Trained on ERR2020 data, evaluated on ERR2020 and mozilla commonvoice test data.
Training procedure
Used Icefall conformer-ctc3 based recipe (https://github.com/k2-fsa/icefall/tree/master/egs/librispeech/ASR/conformer_ctc3)
Training results
TODO
Framework versions
- icefall
- k2
- kaldifeat==1.24
- lhotse==1.15.0
- torch==2.0.0