Search Results for author:
Found 4 papers, 1 papers with code
Breaking the Data Barrier: Towards Robust Speech Translation via Adversarial Stability Training
A standard machine translation system is usually trained on parallel corpus composed of clean text and will perform poorly on text with recognition noise, a gap well known in speech translation community.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
Semantically Consistent Data Augmentation for Neural Machine Translation via Conditional Masked Language Model
In addition, to enhance diversity, we incorporate the idea of soft word substitution for data augmentation which replaces a word with a probabilistic distribution over the vocabulary.
A Paradigm Shift: The Future of Machine Translation Lies with Large Language Models
We conclude by emphasizing the critical role of LLMs in guiding the future evolution of MT and offer a roadmap for future exploration in the sector.
A Hybrid System for NLPTEA-2020 CGED Shared Task
As a result, among the six tracks in the shared task, our system performs well in the correction tracks: measured in F1 score, we rank first, with the highest precision, in the TOP3 correction track and third in the TOP1 correction track, also with the highest precision.
