no code implementations • 19 Aug 2024 • Jaejun Lee, Yoori Oh, Injune Hwang, Kyogu Lee
This paper delves into the emerging field of face-based voice conversion, leveraging the unique relationship between an individual's facial features and their vocal characteristics.
1 code implementation • 10 May 2024 • Jaejun Lee, Minsung Hwang, Joyce Jiyoung Whang
While a number of knowledge graph representation learning (KGRL) methods have been proposed over the past decade, very few theoretical analyses have been conducted on them.
1 code implementation • 31 May 2023 • Jaejun Lee, Chanyoung Chung, Joyce Jiyoung Whang
In this paper, we propose an INductive knowledge GRAph eMbedding method, InGram, that can generate embeddings of new relations as well as new entities at inference time.
1 code implementation • 29 May 2023 • Chanyoung Chung, Jaejun Lee, Joyce Jiyoung Whang
By learning compact representations of triplets and qualifiers and feeding them into the transformers, we reduce the computation cost of using transformers.
2 code implementations • EMNLP (NLPOSS) 2020 • Raphael Tang, Jaejun Lee, Afsaneh Razi, Julia Cambre, Ian Bicking, Jofish Kaye, Jimmy Lin
We describe Howl, an open-source wake word detection toolkit with native support for open speech datasets, like Mozilla Common Voice and Google Speech Commands.
Ranked #4 on
Keyword Spotting
on Google Speech Commands
1 code implementation • ACL 2020 • Raphael Tang, Jaejun Lee, Ji Xin, Xinyu Liu, Yao-Liang Yu, Jimmy Lin
In natural language processing, a recently popular line of work explores how to best report the experimental results of neural networks.
3 code implementations • ACL 2020 • Ji Xin, Raphael Tang, Jaejun Lee, Yao-Liang Yu, Jimmy Lin
Large-scale pre-trained language models such as BERT have brought significant improvements to NLP applications.
no code implementations • 8 Nov 2019 • Jaejun Lee, Raphael Tang, Jimmy Lin
We show that only a fourth of the final layers need to be fine-tuned to achieve 90% of the original quality.
1 code implementation • IJCNLP 2019 • Jaejun Lee, Raphael Tang, Jimmy Lin
Used for simple commands recognition on devices from smart speakers to mobile phones, keyword spotting systems are everywhere.
1 code implementation • 30 Oct 2018 • Jaejun Lee, Raphael Tang, Jimmy Lin
Overall, our robust, cross-device implementation for keyword spotting realizes a new paradigm for serving neural network applications, and one of our slim models reduces latency by 66% with a minimal decrease in accuracy of 4% from 94% to 90%.
no code implementations • 24 Aug 2014 • Jaejun Lee, Taeseon Yun
This paper suggests an effective method for facial recognition using fuzzy theory and Shannon entropy.