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---
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
type: audio
metrics:
- name: Wer
type: wer
value: 12.1
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# 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: 23.2
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` or `build.bat`)
- run docker container (`run.sh`or `run.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 340 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 |