22 citations · 22 across the 4 of their papers we have counts for
4 papers
NEST-RQ: Next Token Prediction for Speech Self-Supervised Pre-Training
Minglun Han, Ye Bai, Chen Shen +6
Speech self-supervised pre-training can effectively improve the performance of downstream tasks. However, previous self-supervised learning (SSL) methods for speech, such as HuBERT…
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…
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…