1 citations · 2 across the 6 of their papers we have counts for
6 papers
Stabilizing Instruction Supervision for Instruct-TTS via Controllable Diversification and Drift Filtering
Yizhong Geng, Kecan Mao, Qifei Li +6
Instruct-TTS systems expand structured style labels into natural-language training instructions through LLM rewriting, yet we find that over 40% of unconstrained rewrites contain s…
RRPO: Robust Reward Policy Optimization for LLM-based Emotional TTS
Cong Wang, Changfeng Gao, Yang Xiang +7
Differentiable reinforcement learning (RL) frameworks like DiffRO offer a powerful approach for controllable text-to-speech (TTS), but are vulnerable to reward hacking, particularl…
Multi-Loss Learning for Speech Emotion Recognition with Energy-Adaptive Mixup and Frame-Level Attention
Cong Wang, Yizhong Geng, Yuhua Wen +7
Speech emotion recognition (SER) is an important technology in human-computer interaction. However, achieving high performance is challenging due to emotional complexity and scarce…
HQ-SVC: Towards High-Quality Zero-Shot Singing Voice Conversion in Low-Resource Scenarios
Bingsong Bai, Yizhong Geng, Fengping Wang +4
Zero-shot singing voice conversion (SVC) transforms a source singer's timbre to an unseen target speaker's voice while preserving melodic content without fine-tuning. Existing meth…
Enhancing Modal Fusion by Alignment and Label Matching for Multimodal Emotion Recognition
Qifei Li, Yingming Gao, Yuhua Wen +2
To address the limitation in multimodal emotion recognition (MER) performance arising from inter-modal information fusion, we propose a novel MER framework based on multitask learn…
Frame-level emotional state alignment method for speech emotion recognition
Qifei Li, Yingming Gao, Cong Wang +4
Speech emotion recognition (SER) systems aim to recognize human emotional state during human-computer interaction. Most existing SER systems are trained based on utterance-level la…