4 citations · 6 across the 8 of their papers we have counts for
4 papers · 1 filter
Adapting Large Language Model with Speech for Fully Formatted End-to-End Speech Recognition
Shaoshi Ling, Yuxuan Hu, Shuangbei Qian +5
Most end-to-end (E2E) speech recognition models are composed of encoder and decoder blocks that perform acoustic and language modeling functions. Pretrained large language models (…
Pre-training End-to-end ASR Models with Augmented Speech Samples Queried by Text
Eric Sun, Jinyu Li, Jian Xue +1
In end-to-end automatic speech recognition system, one of the difficulties for language expansion is the limited paired speech and text training data. In this paper, we propose a n…
DualHSIC: HSIC-Bottleneck and Alignment for Continual Learning
Zifeng Wang, Zheng Zhan, Yifan Gong +4
Rehearsal-based approaches are a mainstay of continual learning (CL). They mitigate the catastrophic forgetting problem by maintaining a small fixed-size buffer with a subset of da…
Building High-accuracy Multilingual ASR with Gated Language Experts and Curriculum Training
Eric Sun, Jinyu Li, Yuxuan Hu +8
We propose gated language experts and curriculum training to enhance multilingual transformer transducer models without requiring language identification (LID) input from users dur…