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--- |
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language: |
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- et |
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license: apache-2.0 |
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metrics: |
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- wer |
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model-index: |
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- name: conformer-ctc et |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: ERR2020 |
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type: audio |
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metrics: |
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- name: Wer |
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type: wer |
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value: 12.1 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# conformer-ctc et |
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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 |
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- WER on ERR2020: 12.1 |
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- WER on mozilla commonvoice_11: 23.2 |
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For usage: |
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- clone this repo (`git clone https://huggingface.co/rristo/icefall_conformer_ctc3_et`) |
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- go to repo (`cd icefall_conformer_ctc3_et`) |
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- build docker image for needed libraries (`build.sh` or `build.bat`) |
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- run docker container (`run.sh`or `run.sh`). This mounts current directory |
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- run notebook `err2020/conformer_ctc3_usage.ipynb` for example usage |
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- currently expects audio to be in .wav format |
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## Model description |
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ASR model for Estonian, uses Estonian Public Broadcasting data ERR2020 data (around 340 hours of audio) |
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## Intended uses & limitations |
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Pretty much a toy model, trained on limited amount of data. Might not work well on data out of domain |
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(especially spontaneous/noisy data). |
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## Training and evaluation data |
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Trained on ERR2020 data, evaluated on ERR2020 and mozilla commonvoice test data. |
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## Training procedure |
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Used Icefall conformer-ctc3 based recipe (https://github.com/k2-fsa/icefall/tree/master/egs/librispeech/ASR/conformer_ctc3) |
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### Training results |
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TODO |
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### Framework versions |
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- icefall |
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- k2 |
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- kaldifeat==1.24 |
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- lhotse==1.15.0 |
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- torch==2.0.0 |
