This work introduces AffectDF, the most comprehensive benchmark for emotionally expressive speech deepfakes, spanning TTS, VC, emotional VC, and LALM-based spoofing attacks across both acted and spontaneous emotional speech.
A speech enhancement framework that jointly models Mel-spectrogram and complex spectrogram in a dual-path architecture for improved ASR performance and higher-quality speech reconstruction, and demonstrates consistent improvements in speech fidelity, perceptual quality, and ASR performance.
Xing-Chen Li, Zi-Qian Wang, Zi-Kai Liu et al.· 0 citations
This work proposes TurnFSM, an LLM-based state prediction framework that internalizes turn control as explicit finite-state transitions, unifying streaming semantic VAD and utterance-level rejection, and introduces a first-order state transition mechanism that enforces the dependency on only the previous state during t...
Zhi-Wei Lin, Tian-Jiao Du, Qiao-Chu Huang et al.· 2 citations
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