2 citations · 5 across the 4 of their papers we have counts for
4 papers
EM-Network: Oracle Guided Self-distillation for Sequence Learning
Ji Won Yoon, Sunghwan Ahn, Hyeonseung Lee +3
We introduce EM-Network, a novel self-distillation approach that effectively leverages target information for supervised sequence-to-sequence (seq2seq) learning. In contrast to con…
Inter-KD: Intermediate Knowledge Distillation for CTC-Based Automatic Speech Recognition
Ji Won Yoon, Beom Jun Woo, Sunghwan Ahn +2
Recently, the advance in deep learning has brought a considerable improvement in the end-to-end speech recognition field, simplifying the traditional pipeline while producing promi…
Oracle Teacher: Leveraging Target Information for Better Knowledge Distillation of CTC Models
Ji Won Yoon, Hyung Yong Kim, Hyeonseung Lee +2
Knowledge distillation (KD), best known as an effective method for model compression, aims at transferring the knowledge of a bigger network (teacher) to a much smaller network (st…
Speech Intention Understanding in a Head-final Language: A Disambiguation Utilizing Intonation-dependency
Won Ik Cho, Hyeon Seung Lee, Ji Won Yoon +2
For a large portion of real-life utterances, the intention cannot be solely decided by either their semantic or syntactic characteristics. Although not all the sociolinguistic and…