Explore different way to mix speech model(wav2vec2, hubert) and nlp model(BART,T5,GPT) together.
Implementation of:
Large-Scale Self- and Semi-Supervised Learning for Speech Translation - ACL2021
Multilingual Speech Translation with Efficient Finetuning of Pretrained Models - ACL2021
Lightweight Adapter Tuning for Multilingual Speech Translation - Interspeech 2021
Improving Speech Translation by Understanding and Learning from the Auxiliary Text Translation Task - ACL2021
A General Multi-Task Learning Framework to Leverage Text Data for Speech to Text Tasks - ICASSP 2021
pip install speechmixgit clone and cd into this project.
pip install -e .WANDB_PROJECT=amazing
python train.py --speech_model_config wav2vec2 \
--nlp_model_config facebook/bart-base \
--SpeechMixEED \
--dataset librispeech_asr \
--field clean \
--train_split train.100 \
--test_split validation \
--batch 3 \
--grad_accum 20 \
--epoch 30 \
--worker 15 \
--share_layer_ratio 0 \
--down_scale 2 \
--lr 4e-5 \
--warmup_steps 500 \
--wandb \
--notes base