Topic
speech detection
New Temporal Pyramid Model Enhances Spoofed Speech Detection for Voice Security Systems
Researchers introduced a Temporal Pyramid Adapter for spoofed speech detection that uses parallel temporal convolutions with varying receptive fields to capture multi-scale cues. The model achieved a 99.24% AUC and 3.87% EER on the PartialSpoof dataset, significantly outperforming existing methods like LCNN-BLSTM (9.87% EER) and TRACE (8.08% EER). The work highlights the potential for improving voice authentication security but notes performance degradation under domain and language shifts.
Training-Free Framework Uses XAI and Multimodal LLMs to Generate Grounded Explanations for Speech Deepfake Detection
Researchers propose a training-free explanation framework that integrates XAI evidence with multimodal large language models to generate grounded and specific explanations for speech deepfake detection. Using the PartialSpoof dataset, the method increases inside accuracy by over 45%, verified through human evaluation and faithfulness checks.