Clone the repository and create conda environment by running conda env create -f environment.yml
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Filter noise from synthetic speech translation dataset - (source, source_asr, source_pos, target). Source and Source_asr pairs that are not similar are dropped.
python speech_translation.py filter --workdir= --source= --source_asr= --target= --source_pos= --result_source= --result_source_asr --result_target --result_source_pos
Learn suffix noise model from filtered synthetic dataset.
python speech_translation.py learn_noise_model --workdir=workdir --source= --source_pos= --source_asr= --result_model=
Apply suffix noise model to any parallel dataset.
python speech_translation.py apply_noise_model --source= --source_pos= --target= --result_source= --result_target= --noise_model=
Model ASR word split/merges.
python speech_translation.py generate_split_merge --source= --target= --result_target= --result_source=