4 papers
Rare Word Recognition and Translation Without Fine-Tuning via Task Vector in Speech Models
Ruihao Jing, Cheng Gong, Yu Jiang +5
Rare words remain a critical bottleneck for speech-to-text systems. While direct fine-tuning improves recognition of target words, it often incurs high cost, catastrophic forgettin…
Perturbation Self-Supervised Representations for Cross-Lingual Emotion TTS: Stage-Wise Modeling of Emotion and Speaker
Cheng Gong, Chunyu Qiang, Tianrui Wang +7
Cross-lingual emotional text-to-speech (TTS) aims to produce speech in one language that captures the emotion of a speaker from another language while maintaining the target voice'…
Efficient Emotion and Speaker Adaptation in LLM-Based TTS via Characteristic-Specific Partial Fine-Tuning
Tianrui Wang, Meng Ge, Cheng Gong +11
While LLM-based TTS models exhibit zero-shot emotion and speaker cloning, their cloning fidelity and pronunciation clarity degrade on unseen domains. Fine-tuning is essential for a…
Expressive Prompting: Improving Emotion Intensity and Speaker Consistency in Zero-Shot TTS
Haoyu Wang, Chunyu Qiang, Tianrui Wang +6
Recent advancements in speech synthesis have enabled large language model (LLM)-based systems to perform zero-shot generation with controllable content, timbre, speaker identity, a…