5 papers
ToolDF: Tool-Integrated Reasoning for Mixed-Authenticity Audio Deepfake Detection
Taewoo Kim, Young Han Lee, Nam In Park +1
Audio deepfake detection is commonly formulated as clip-level binary classification of single-domain audio. However, real-world manipulated audio can exhibit mixed authenticity, wh…
Lightweight Wasserstein Audio-Visual Model for Unified Speech Enhancement and Separation
Jisoo Park, Seonghak Lee, Guisik Kim +2
Speech Enhancement (SE) and Speech Separation (SS) have traditionally been treated as distinct tasks in speech processing. However, real-world audio often involves both background…
Instance-Specific Test-Time Training for Speech Editing in the Wild
Taewoo Kim, Uijong Lee, Hayoung Park +3
Speech editing systems aim to naturally modify speech content while preserving acoustic consistency and speaker identity. However, previous studies often struggle to adapt to unsee…
Naturalness-Aware Curriculum Learning with Dynamic Temperature for Speech Deepfake Detection
Taewoo Kim, Guisik Kim, Choongsang Cho +1
Recent advances in speech deepfake detection (SDD) have significantly improved artifacts-based detection in spoofed speech. However, most models overlook speech naturalness, a cruc…
Period Singer: Integrating Periodic and Aperiodic Variational Autoencoders for Natural-Sounding End-to-End Singing Voice Synthesis
Taewoo Kim, Choongsang Cho, Young Han Lee
In this paper, we present Period Singer, a novel end-to-end singing voice synthesis (SVS) model that utilizes variational inference for periodic and aperiodic components, aimed at…