activity
20102024
most citedBest Practices for Scientific Computing

754 citations · 3.2k across the 112 of their papers we have counts for

collaborators

113 papers

cs.MM2024

SyncFlow: Toward Temporally Aligned Joint Audio-Video Generation from Text

Haohe Liu, Gael Le Lan, Xinhao Mei +7

Video and audio are closely correlated modalities that humans naturally perceive together. While recent advancements have enabled the generation of audio or video from text, produc…

eess.AS2024

AudioSetCaps: An Enriched Audio-Caption Dataset using Automated Generation Pipeline with Large Audio and Language Models

Jisheng Bai, Haohe Liu, Mou Wang +5

With the emergence of audio-language models, constructing large-scale paired audio-language datasets has become essential yet challenging for model development, primarily due to th…

eess.AS2024

PSELDNets: Pre-trained Neural Networks on a Large-scale Synthetic Dataset for Sound Event Localization and Detection

Jinbo Hu, Yin Cao, Ming Wu +5

Sound event localization and detection (SELD) has seen substantial advancements through learning-based methods. These systems, typically trained from scratch on specific datasets,…

eess.AS2024

A decade of DCASE: Achievements, practices, evaluations and future challenges

Annamaria Mesaros, Romain Serizel, Toni Heittola +2

This paper introduces briefly the history and growth of the Detection and Classification of Acoustic Scenes and Events (DCASE) challenge, workshop, research area and research commu…

cs.SD2024

The Sounds of Home: A Speech-Removed Residential Audio Dataset for Sound Event Detection

Gabriel Bibbó, Thomas Deacon, Arshdeep Singh +1

This paper presents a residential audio dataset to support sound event detection research for smart home applications aimed at promoting wellbeing for older adults. The dataset is…

eess.AS2024

Exploring Differences between Human Perception and Model Inference in Audio Event Recognition

Yizhou Tan, Yanru Wu, Yuanbo Hou +5

Audio Event Recognition (AER) traditionally focuses on detecting and identifying audio events. Most existing AER models tend to detect all potential events without considering thei…