1 citations · 1 across the 9 of their papers we have counts for
9 papers · 1 filter
Covo-Audio Technical Report
Wenfu Wang, Chenxing Li, Liqiang Zhang +23
In this work, we present Covo-Audio, a 7B-parameter end-to-end LALM that directly processes continuous audio inputs and generates audio outputs within a single unified architecture…
Scalable Neural Vocoder from Range-Null Space Decomposition
Andong Li, Tong Lei, Zhihang Sun +4
Although deep neural networks have facilitated significant progress of neural vocoders in recent years, they usually suffer from intrinsic challenges like opaque modeling, inflexib…
Gen-SER: When the generative model meets speech emotion recognition
Taihui Wang, Jinzheng Zhao, Rilin Chen +3
Speech emotion recognition (SER) is crucial in speech understanding and generation. Most approaches are based on either classification models or large language models. Different fr…
BridgeVoC: Revitalizing Neural Vocoder from a Restoration Perspective
Andong Li, Tong Lei, Rilin Chen +5
This paper revisits the neural vocoder task through the lens of audio restoration and propose a novel diffusion vocoder called BridgeVoC. Specifically, by rank analysis, we compare…
AudioRAG+: Feedback-driven Retrieval-augmented Audio Generation with Large Audio Language Models
Junqi Zhao, Chenxing Li, Jinzheng Zhao +4
We propose a general feedback-driven retrieval-augmented generation (RAG) approach that leverages Large Audio Language Models (LALMs) to address the missing or imperfect synthesis…
Target matching based generative model for speech enhancement
Taihui Wang, Rilin Chen, Tong Lei +4
The design of mean and variance schedules for the perturbed signal is a fundamental challenge in generative models. While score-based and Schrödinger bridge-based models require ca…