collaborators

6 papers

cs.SD2026

StellarTTS: Sparse Temporal Embedding for Low-Latency and Robust Speech Synthesis

Kaicheng Luo, Xuefei Gong, Yutao Sun +6

The trade-off between robustness, latency, and prosody critically challenges text-to-speech (TTS) systems. Autoregressive models, despite fidelity, are slow and error-prone; non-au…

eess.AS2026

AudioCALM: Continuous Autoregressive Language Modeling for Universal Audio Generation

Huadai Liu, Kaicheng Luo, Wen Wang +4

Unifying speech, sound, and music generation in one model is hindered by tradeoffs between fidelity, end-to-end training, in-context conditioning, and variable-length synthesis tha…

eess.AS2026

STAR-VAE: Structured Topology-Aware Regularization for Audio Reconstruction and Generation

Huadai Liu, Wen Wang, Kaicheng Luo +3

Continuous Variational Autoencoders (VAEs) serve as the fundamental continuous tokenizer for modern neural audio generation systems, enabling high-fidelity reconstruction while pro…

cs.SD2026

PrismAudio: Decomposed Chain-of-Thoughts and Multi-dimensional Rewards for Video-to-Audio Generation

Huadai Liu, Kaicheng Luo, Wen Wang +6

Video-to-Audio (V2A) generation requires balancing four critical perceptual dimensions: semantic consistency, audio-visual temporal synchrony, aesthetic quality, and spatial accura…

eess.AS2025

ThinkSound: Chain-of-Thought Reasoning in Multimodal Large Language Models for Audio Generation and Editing

Huadai Liu, Kaicheng Luo, Jialei Wang +4

While end-to-end video-to-audio generation has greatly improved, producing high-fidelity audio that authentically captures the nuances of visual content remains challenging. Like p…

eess.AS2025

OmniAudio: Generating Spatial Audio from 360-Degree Video

Huadai Liu, Tianyi Luo, Kaicheng Luo +11

Traditional video-to-audio generation techniques primarily focus on perspective video and non-spatial audio, often missing the spatial cues necessary for accurately representing so…