Artificial Intelligence #spoofed speech#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.
Jun 17, 2026 1 source
