Automatic Speech Recognition for Belarusian language
Fine-tuned version of facebook/wav2vec2-base on mozilla-foundation/common_voice_8_0 be
dataset.
Train
, Dev
, Test
splits were used as they are present in the dataset. No additional data was used from Validated
split,
only 1 voicing of each sentence was used - the way the data was split by CommonVoice CorporaCreator.
To build a better model one can use additional voicings from Validated
split for sentences already present in Train
, Dev
, Test
splits,
i.e. enlarge mentioned splits.
Language model was built using KenLM.
5-gram Language model was built on sentences from Train + (Other - Dev - Test)
splits of mozilla-foundation/common_voice_8_0 be
dataset.
Source code is available here.
Run model in a browser
This page contains interactive demo widget that lets you test this model right in a browser.
However, this widget uses Acoustic model only without Language model that significantly improves overall performance.
You can play with full pipeline of Acoustic model + Language model on the following spaces page (also works from browser).
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Dataset used to train ales/wav2vec2-cv-be
Space using ales/wav2vec2-cv-be 1
Evaluation results
- Dev WER on Common Voice 8self-reported17.610
- Test WER on Common Voice 8self-reported18.700
- Dev WER (with LM) on Common Voice 8self-reported11.500
- Test WER (with LM) on Common Voice 8self-reported12.400