Speaker verification (SV) models are commonly assumed to better capture nuances among speaker characteristics as verification accuracy improves, leading to their widespread use as automated proxies for human voice similarity in speech generation tasks. However, by establishing a human perceptual alignment metric and co...
Szu-Chi Chen, Jia-Tang Dong, Yi-Cheng Lin et al.· 0 citations
GDP-RAG is proposed, a plan-based framework that targets only the information delta based on three simple design choices, and achieves the highest accuracy among all compared systems while maintaining a cost-of-pass of 0.51.
Wei-Chieh Chou, Xuan-Bo Chen, Jian-Zhe Lin et al.· arXiv.org· 3 citations
The Teaching Monster Challenge is introduced, the first instructional video generation benchmark to treat the learner persona as an explicit evaluation criterion and release the benchmark, rubric, and human judgments as a testbed for both teaching systems and automatic judges.
Yi-Cheng Lin, Yu-Kai Guo, Szu-Chi Chen et al.· 0 citations
The results show that a small, carefully chosen activation set can switch on test-time scaling inside a frozen ASR model without corrupting the model itself, converting fixed per-utterance compute into input-dependent compute where it is most needed.
Ho-Lam Chung, Yiming Chen, Dau-Cheng Lyu et al.· 0 citations
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