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cs.CL2022★ 1 cited
Bridging Speech and Textual Pre-trained Models with Unsupervised ASR
Jiatong Shi, Chan-Jan Hsu, Holam Chung +5
Spoken language understanding (SLU) is a task aiming to extract high-level semantics from spoken utterances. Previous works have investigated the use of speech self-supervised mode…
cs.CL2022
T5lephone: Bridging Speech and Text Self-supervised Models for Spoken Language Understanding via Phoneme level T5
Chan-Jan Hsu, Ho-Lam Chung, Hung-yi Lee +1
In Spoken language understanding (SLU), a natural solution is concatenating pre-trained speech models (e.g. HuBERT) and pretrained language models (PLM, e.g. T5). Most previous wor…
cs.CL2022
XDBERT: Distilling Visual Information to BERT from Cross-Modal Systems to Improve Language Understanding
Chan-Jan Hsu, Hung-yi Lee, Yu Tsao
Transformer-based models are widely used in natural language understanding (NLU) tasks, and multimodal transformers have been effective in visual-language tasks. This study explore…