most citedSpeech-FT: Merging Pre-trained And Fine-Tuned Speech Representation Models For Cross-Task Generalization

3 citations · 3 across the 2 of their papers we have counts for

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cs.CL2026★ 3 cited

Speech-FT: Merging Pre-trained And Fine-Tuned Speech Representation Models For Cross-Task Generalization

Tzu-Quan Lin, Wei-Ping Huang, Hao Tang +1

Fine-tuning speech representation models can enhance performance on specific tasks but often compromises their cross-task generalization ability. This degradation is often caused b…

cs.CL2025

Identifying Speaker Information in Feed-Forward Layers of Self-Supervised Speech Transformers

Tzu-Quan Lin, Hsi-Chun Cheng, Hung-yi Lee +1

In recent years, the impact of self-supervised speech Transformers has extended to speaker-related applications. However, little research has explored how these models encode speak…