---
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
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# 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` 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 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