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20242026
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eess.AS2026

Decoupling Conversational Dynamics in Full-Duplex Spoken Models through Reinforcement Learning

Yuxin Li, Donghang Wu, Guan-Ting Lin +4

Recent full-duplex spoken dialogue models have demonstrated compelling progress toward human-like interaction, enabling agents to respond with low latency, produce backchannels, an…

eess.AS2026

Rethinking Entropy Minimization in Test-Time Adaptation for Autoregressive Models

Wei-Ping Huang, Chee-En Yu, Guan-Ting Lin +1

Test-Time Adaptation (TTA) via entropy minimization (EM) has proven effective for classification tasks, yet its application to generative autoregressive models remains theoreticall…

eess.AS2026

Game-Time: Evaluating Temporal Dynamics in Spoken Language Models

Kai-Wei Chang, En-Pei Hu, Chun-Yi Kuan +7

Conversational Spoken Language Models (SLMs) are emerging as a promising paradigm for real-time speech interaction. However, their capacity of temporal dynamics, including the abil…

eess.AS2026

Full-Duplex-Bench v1.5: Evaluating Overlap Handling for Full-Duplex Speech Models

Guan-Ting Lin, Shih-Yun Shan Kuan, Qirui Wang +4

Full-duplex spoken dialogue systems promise to transform human-machine interaction from a rigid, turn-based protocol into a fluid, natural conversation. However, the central challe…

eess.AS2024

Continual Test-time Adaptation for End-to-end Speech Recognition on Noisy Speech

Guan-Ting Lin, Wei-Ping Huang, Hung-yi Lee

Deep Learning-based end-to-end Automatic Speech Recognition (ASR) has made significant strides but still struggles with performance on out-of-domain samples due to domain shifts in…

eess.AS2024

Property Neurons in Self-Supervised Speech Transformers

Tzu-Quan Lin, Guan-Ting Lin, Hung-yi Lee +1

There have been many studies on analyzing self-supervised speech Transformers, in particular, with layer-wise analysis. It is, however, desirable to have an approach that can pinpo…