36 citations · 49 across the 6 of their papers we have counts for
4 papers · 1 filter
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…
Improved Spoken Document Summarization with Coverage Modeling Techniques
Kuan-Yu Chen, Shih-Hung Liu, Berlin Chen +1
Extractive summarization aims at selecting a set of indicative sentences from a source document as a summary that can express the major theme of the document. A general consensus o…
Leveraging Word Embeddings for Spoken Document Summarization
Kuan-Yu Chen, Shih-Hung Liu, Hsin-Min Wang +2
Owing to the rapidly growing multimedia content available on the Internet, extractive spoken document summarization, with the purpose of automatically selecting a set of representa…