activity
20202026
most citedFish Tracking, Counting, and Behaviour Analysis in Digital Aquaculture: A Comprehensive Survey

95 citations · 229 across the 34 of their papers we have counts for

collaborators
Showing 2025Show all

7 papers · 1 filter

cs.SD2025

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…

eess.AS2025

Region-Specific Audio Tagging for Spatial Sound

Jinzheng Zhao, Yong Xu, Haohe Liu +6

Audio tagging aims to label sound events appearing in an audio recording. In this paper, we propose region-specific audio tagging, a new task which labels sound events in a given r…

cs.SD2025

DreamAudio: Customized Text-to-Audio Generation with Diffusion Models

Yi Yuan, Xubo Liu, Haohe Liu +5

With the development of large-scale diffusion-based and language-modeling-based generative models, impressive progress has been achieved in text-to-audio generation. Despite produc…

cs.SD2025

AudioTurbo: Fast Text-to-Audio Generation with Rectified Diffusion

Junqi Zhao, Jinzheng Zhao, Haohe Liu +5

Diffusion models have significantly improved the quality and diversity of audio generation but are hindered by slow inference speed. Rectified flow enhances inference speed by lear…

cs.SD2025★ 6 cited

EnvSDD: Benchmarking Environmental Sound Deepfake Detection

Han Yin, Yang Xiao, Rohan Kumar Das +4

Audio generation systems now create very realistic soundscapes that can enhance media production, but also pose potential risks. Several studies have examined deepfakes in speech o…

eess.AS2025

Exploring the User Experience of AI-Assisted Sound Searching Systems for Creative Workflows

Haohe Liu, Thomas Deacon, Wenwu Wang +2

Locating the right sound effect efficiently is an important yet challenging topic for audio production. Most current sound-searching systems rely on pre-annotated audio labels crea…

cs.LG2025

Audio-Visual Class-Incremental Learning for Fish Feeding intensity Assessment in Aquaculture

Meng Cui, Xianghu Yue, Xinyuan Qian +5

Fish Feeding Intensity Assessment (FFIA) is crucial in industrial aquaculture management. Recent multi-modal approaches have shown promise in improving FFIA robustness and efficien…