Word boosting / context biasing
Hi Nvidia team,
Thanks for publishing the model. I am wondering if we could increase the probability of certain words without training/finetuning the model?
I've tried changing the decoding strategy to "flashlight" and do word boosting but the model (TDT) does not support that. Is there any other way? Thank you.
Hi,
We are currently working on word/phrase boosting in a shallow-fusion mode for RNNT/TDT models (there is no need for additional training/finetuning; you need only a list with your key phrases). I hope this option will appear in the NeMo framework within 1-2 months. At the moment, you can use NGPU-LM for the shallow-fusion (https://github.com/NVIDIA/NeMo/pull/12729), but it needs training text data to build ngram-lm and does not work as a fair word boosting approach. It works as a context-biasing for the specific data domain.
Thank you @aandrusenko
Hi，
What should I do if I want to transcribe in real time?