22 citations · 46 across the 18 of their papers we have counts for
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Data Commons
Ramanathan V. Guha, Prashanth Radhakrishnan, Bo Xu +10
Publicly available data from open sources (e.g., United States Census Bureau (Census), World Health Organization (WHO), Intergovernmental Panel on Climate Change (IPCC)) are vital…
A Knowledge-enhanced Two-stage Generative Framework for Medical Dialogue Information Extraction
Zefa Hu, Ziyi Ni, Jing Shi +2
This paper focuses on term-status pair extraction from medical dialogues (MD-TSPE), which is essential in diagnosis dialogue systems and the automatic scribe of electronic medical…
P-vectors: A Parallel-Coupled TDNN/Transformer Network for Speaker Verification
Xiyuan Wang, Fangyuan Wang, Bo Xu +2
Typically, the Time-Delay Neural Network (TDNN) and Transformer can serve as a backbone for Speaker Verification (SV). Both of them have advantages and disadvantages from the persp…
X-LLM: Bootstrapping Advanced Large Language Models by Treating Multi-Modalities as Foreign Languages
Feilong Chen, Minglun Han, Haozhi Zhao +4
Large language models (LLMs) have demonstrated remarkable language abilities. GPT-4, based on advanced LLMs, exhibits extraordinary multimodal capabilities beyond previous visual l…
VILAS: Exploring the Effects of Vision and Language Context in Automatic Speech Recognition
Ziyi Ni, Minglun Han, Feilong Chen +4
Enhancing automatic speech recognition (ASR) performance by leveraging additional multimodal information has shown promising results in previous studies. However, most of these wor…
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…
Knowledge Transfer from Pre-trained Language Models to Cif-based Speech Recognizers via Hierarchical Distillation
Minglun Han, Feilong Chen, Jing Shi +2
Large-scale pre-trained language models (PLMs) have shown great potential in natural language processing tasks. Leveraging the capabilities of PLMs to enhance automatic speech reco…