activity
20232026
most citedEEND-DEMUX: End-to-End Neural Speaker Diarization via Demultiplexed Speaker Embeddings

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2026

MD-ProTector: Positioning Multiple Data-Driven Prototypes for LLM-Generated Text Detection

Jinmo Han, Jimin Hong, Chanyeong Moon +3

As LLM-generated content becomes more sophisticated, detection systems for distinguishing those texts from human-written text must operate at scale while handling diverse writing s…

cs.CV2025

Semantic-Aware Reconstruction Error for Detecting AI-Generated Images

Ju Yeon Kang, Jaehong Park, Semin Kim +2

Recently, AI-generated image detection has gained increasing attention, as the rapid advancement of image generation technologies has raised serious concerns about their potential…

eess.AS2025

FADEL: Uncertainty-aware Fake Audio Detection with Evidential Deep Learning

Ju Yeon Kang, Ji Won Yoon, Semin Kim +2

Recently, fake audio detection has gained significant attention, as advancements in speech synthesis and voice conversion have increased the vulnerability of automatic speaker veri…

eess.AS2024

HILCodec: High-Fidelity and Lightweight Neural Audio Codec

Sunghwan Ahn, Beom Jun Woo, Min Hyun Han +2

The recent advancement of end-to-end neural audio codecs enables compressing audio at very low bitrates while reconstructing the output audio with high fidelity. Nonetheless, such…

eess.AS2023★ 1 cited

EEND-DEMUX: End-to-End Neural Speaker Diarization via Demultiplexed Speaker Embeddings

Sung Hwan Mun, Min Hyun Han, Canyeong Moon +1

In recent years, there have been studies to further improve the end-to-end neural speaker diarization (EEND) systems. This letter proposes the EEND-DEMUX model, a novel framework u…