14 papers
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…
SLAP: Scalable Language-Audio Pretraining with Variable-Duration Audio and Multi-Objective Training
Xinhao Mei, Gael Le Lan, Haohe Liu +5
Contrastive language-audio pretraining (CLAP) has achieved notable success in learning semantically rich audio representations and is widely adopted for various audio-related tasks…
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…
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…
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…
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…