5 papers
A Hybrid Discriminative and Generative System for Universal Speech Enhancement
Yinghao Liu, Chengwei Liu, Xiaotao Liang +3
Universal speech enhancement aims at handling inputs with various speech distortions and recording conditions. In this work, we propose a novel hybrid architecture that synergizes…
Contextual Biasing for LLM-Based ASR with Hotword Retrieval and Reinforcement Learning
YuXiang Kong, JunFeng Hou, Jian Tang +3
Large language model (LLM)-based automatic speech recognition (ASR) has recently achieved strong performance across diverse tasks, yet contextual biasing for named entities and hot…
QuarkAudio Technical Report
Chengwei Liu, Haoyin Yan, Shaofei Xue +5
Many existing audio processing and generation models rely on task-specific architectures, resulting in fragmented development efforts and limited extensibility. It is therefore pro…
UniTok-Audio: A Unified Audio Generation Framework via Generative Modeling on Discrete Codec Tokens
Chengwei Liu, Haoyin Yan, Shaofei Xue +5
Generative modeling has recently achieved remarkable success across text, image, and audio domains, demonstrating powerful capabilities for unified representation learning. However…
OmniAvatar: Efficient Audio-Driven Avatar Video Generation with Adaptive Body Animation
Qijun Gan, Ruizi Yang, Jianke Zhu +2
Significant progress has been made in audio-driven human animation, while most existing methods focus mainly on facial movements, limiting their ability to create full-body animati…