271 citations · 278 across the 6 of their papers we have counts for
6 papers
Seed-ASR: Understanding Diverse Speech and Contexts with LLM-based Speech Recognition
Ye Bai, Jingping Chen, Jitong Chen +52
Modern automatic speech recognition (ASR) model is required to accurately transcribe diverse speech signals (from different domains, languages, accents, etc) given the specific con…
Matching-based Term Semantics Pre-training for Spoken Patient Query Understanding
Zefa Hu, Xiuyi Chen, Haoran Wu +5
Medical Slot Filling (MSF) task aims to convert medical queries into structured information, playing an essential role in diagnosis dialogue systems. However, the lack of sufficien…
Complex Dynamic Neurons Improved Spiking Transformer Network for Efficient Automatic Speech Recognition
Minglun Han, Qingyu Wang, Tielin Zhang +3
The spiking neural network (SNN) using leaky-integrated-and-fire (LIF) neurons has been commonly used in automatic speech recognition (ASR) tasks. However, the LIF neuron is still…
Improving End-to-End Contextual Speech Recognition with Fine-Grained Contextual Knowledge Selection
Minglun Han, Linhao Dong, Zhenlin Liang +4
Nowadays, most methods in end-to-end contextual speech recognition bias the recognition process towards contextual knowledge. Since all-neural contextual biasing methods rely on ph…
VLP: A Survey on Vision-Language Pre-training
Feilong Chen, Duzhen Zhang, Minglun Han +4
In the past few years, the emergence of pre-training models has brought uni-modal fields such as computer vision (CV) and natural language processing (NLP) to a new era. Substantia…
CIF-based Collaborative Decoding for End-to-end Contextual Speech Recognition
Minglun Han, Linhao Dong, Shiyu Zhou +1
End-to-end (E2E) models have achieved promising results on multiple speech recognition benchmarks, and shown the potential to become the mainstream. However, the unified structure…