23 citations · 29 across the 13 of their papers we have counts for
3 papers · 1 filter
SpeechCLIP+: Self-supervised multi-task representation learning for speech via CLIP and speech-image data
Hsuan-Fu Wang, Yi-Jen Shih, Heng-Jui Chang +5
The recently proposed visually grounded speech model SpeechCLIP is an innovative framework that bridges speech and text through images via CLIP without relying on text transcriptio…
Learning to Distill: The Essence Vector Modeling Framework
Kuan-Yu Chen, Shih-Hung Liu, Berlin Chen +1
In the context of natural language processing, representation learning has emerged as a newly active research subject because of its excellent performance in many applications. Lea…
Novel Word Embedding and Translation-based Language Modeling for Extractive Speech Summarization
Kuan-Yu Chen, Shih-Hung Liu, Berlin Chen +2
Word embedding methods revolve around learning continuous distributed vector representations of words with neural networks, which can capture semantic and/or syntactic cues, and in…