| --- |
| license: apache-2.0 |
| language: |
| - uk |
| pipeline_tag: automatic-speech-recognition |
| datasets: |
| - mozilla-foundation/common_voice_10_0 |
| - Yehor/openstt-uk |
| metrics: |
| - wer |
| model-index: |
| - name: w2v-bert-uk-v2.1 |
| results: |
| - task: |
| name: Automatic Speech Recognition |
| type: automatic-speech-recognition |
| dataset: |
| name: common_voice_10_0 |
| type: common_voice_10_0 |
| config: uk |
| split: test |
| args: uk |
| metrics: |
| - name: WER |
| type: wer |
| value: 9.0777 |
| - name: CER |
| type: cer |
| value: 1.9839 |
| --- |
| |
| # Flashlight for Ukrainian |
|
|
| ## Community |
|
|
| - Discord: https://bit.ly/discord-uds |
| - Speech Recognition: https://t.me/speech_recognition_uk |
| - Speech Synthesis: https://t.me/speech_synthesis_uk |
|
|
| See other Ukrainian models: https://github.com/egorsmkv/speech-recognition-uk |
|
|
| ## Overview |
|
|
| This repository contains the acoustic model for Ukrainian trained on Flashlight framework: https://github.com/flashlight/flashlight/tree/main/flashlight/app/asr |
|
|
| - Architecture: Conformer (300m params) |
| - Data in train: Common Voice 10 & Voice of America |
| - Trained epochs: 410 |
| - Train time: around a week (RTX A4000) |
|
|
| ## Quality |
|
|
| - WER: 9.0777% (id est the quality is 90.92%) |
| - CER: 1.9839% |
|
|
| ## How to test? |
|
|
| ### Run a container with Flashlight running with CPU |
|
|
| ```bash |
| docker-compose up |
| |
| # and in another termianl |
| docker exec -it flashlight_cpu bash |
| ``` |
|
|
| ### Run |
|
|
| Just with an AM: |
|
|
| ``` |
| /root/flashlight/build/bin/asr/fl_asr_test --am /models/uk_am.bin --datadir '' --emission_dir '' --uselexicon false \ |
| --test /data/rows.lst --tokens /models/tokens.txt --lexicon /models/lexicon.txt --show |
| ``` |
| |
| With an LM: |
| |
| ``` |
| /root/flashlight/build/bin/asr/fl_asr_decode \ |
| --am=/models/uk_am.bin \ |
| --test=/data/labels_absolute.lst \ |
| --maxload=3477 \ |
| --nthread_decoder=2 \ |
| --show \ |
| --showletters \ |
| --lexicon=/models/lexicon.txt \ |
| --uselexicon=false \ |
| --lm=/models/lm_4gram_500k.binary \ |
| --lmtype=kenlm \ |
| --decodertype=wrd \ |
| --beamsize=200 \ |
| --beamsizetoken=200 \ |
| --beamthreshold=20 \ |
| --lmweight=0.75 \ |
| --wordscore=0 \ |
| --eosscore=0 \ |
| --silscore=0 \ |
| --unkscore=0 \ |
| --smearing=max |
| ``` |
|
|
| - **labels_absolute.lst** is from https://github.com/egorsmkv/cv10-uk-testset-clean |
| - **lm_4gram_500k.binary** is from https://huggingface.co/Yehor/kenlm-ukrainian/tree/main/news/lm-4gram-500k |
| |
| ## How to fine-tune on own data? |
| |
| ``` |
| /root/flashlight/build/bin/asr/fl_asr_train continue /models/ --flagsfile /models/train.flags |
| ``` |
| |
| `/models/` must contain .bin files |
| |
| ## Cite this work |
| |
| ``` |
| @misc {smoliakov_2025, |
| author = { {Smoliakov} }, |
| title = { flashlight-uk (Revision 1ac154b) }, |
| year = 2025, |
| url = { https://huggingface.co/Yehor/flashlight-uk }, |
| doi = { 10.57967/hf/4577 }, |
| publisher = { Hugging Face } |
| } |
| ``` |
| |
