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cs.CL2026
Joint Speech and Text Training for LLM-Based End-to-End Spoken Dialogue State Tracking
Katia Vendrame, Bolaji Yusuf, Santosh Kesiraju +3
End-to-end spoken dialogue state tracking (DST) is made difficult by the tandem of having to handle speech input and data scarcity. Combining speech foundation encoders and large l…
cs.CL2025
TS-SUPERB: A Target Speech Processing Benchmark for Speech Self-Supervised Learning Models
Junyi Peng, Takanori Ashihara, Marc Delcroix +4
Self-supervised learning (SSL) models have significantly advanced speech processing tasks, and several benchmarks have been proposed to validate their effectiveness. However, previ…