6 papers
Self-Guidance: Enhancing Neural Codecs via Decoder Manifold Alignment
Xiang Li, Yixuan Zhou, Jingran Xie +2
Neural speech codecs based on Vector-Quantized VAEs (VQ-VAEs) are core audio tokenizers for speech LLMs, yet their reconstruction fidelity is bottlenecked by quantization error. Mo…
Feature-Aligned Speech Watermarking for Robustness to Reconstruction Distortions
Haiyun Li, Shuhai Peng, Zhisheng Zhang +4
Audio watermarking aims to embed identifiable information into audio while remaining imperceptible. Existing methods adopt high-fidelity, low-energy designs to preserve perceptual…
TTS-PRISM: A Perceptual Reasoning and Interpretable Speech Model for Fine-Grained Diagnosis
Xi Wang, Jie Wang, Xingchen Song +8
While generative text-to-speech (TTS) models approach human-level quality, monolithic metrics fail to diagnose fine-grained acoustic artifacts or explain perceptual collapse. To ad…
VoiceMark: Zero-Shot Voice Cloning-Resistant Watermarking Approach Leveraging Speaker-Specific Latents
Haiyun Li, Zhiyong Wu, Xiaofeng Xie +3
Voice cloning (VC)-resistant watermarking is an emerging technique for tracing and preventing unauthorized cloning. Existing methods effectively trace traditional VC models by trai…
Enhancing Generalization of Speech Large Language Models with Multi-Task Behavior Imitation and Speech-Text Interleaving
Jingran Xie, Xiang Li, Hui Wang +4
Large language models (LLMs) have shown remarkable generalization across tasks, leading to increased interest in integrating speech with LLMs. These speech LLMs (SLLMs) typically u…
Leveraging Chain of Thought towards Empathetic Spoken Dialogue without Corresponding Question-Answering Data
Jingran Xie, Shun Lei, Yue Yu +4
Empathetic dialogue is crucial for natural human-computer interaction, allowing the dialogue system to respond in a more personalized and emotionally aware manner, improving user s…