Papers by Zhengxing Chen

2 papers
ReStyle-TTS: Relative and Continuous Style Control for Zero-Shot Speech Synthesis (2026.findings-acl)

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Challenge: Recent controllable zero-shot text-to-speech systems can synthesize speech for unseen speakers from a short reference audio clip, but they also inherit the speaking style present in the reference.
Approach: They propose a framework that enables continuous and reference-relative style control in zero-shot text-to-speech systems by combining style-specific LoRAs with Orthogonal LoRA Fusion.
Outcome: The proposed framework reduces the model's dependence on reference style while preserving text fidelity while maintaining intelligibility and speaker timbre.
Self-Generated Critiques Boost Reward Modeling for Language Models (2025.naacl-long)

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Challenge: Existing reward models produce scalar scores and struggle to incorporate critiques in a natural language format.
Approach: They propose a framework that predicts critiques and rewards using self-generated critiques without extra supervision.
Outcome: The proposed framework improves reward modeling accuracy by 3.7%-7.3% compared to standard reward models and LLM judges.

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