5 citations · 10 across the 7 of their papers we have counts for
7 papers
Joint Feature and Output Distillation for Low-complexity Acoustic Scene Classification
Haowen Li, Ziyi Yang, Mou Wang +4
This report presents a dual-level knowledge distillation framework with multi-teacher guidance for low-complexity acoustic scene classification (ASC) in DCASE2025 Task 1. We propos…
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…
Sound event localization and classification using WASN in Outdoor Environment
Dongzhe Zhang, Jianfeng Chen, Jisheng Bai +4
Deep learning-based sound event localization and classification is an emerging research area within wireless acoustic sensor networks. However, current methods for sound event loca…
Description on IEEE ICME 2024 Grand Challenge: Semi-supervised Acoustic Scene Classification under Domain Shift
Jisheng Bai, Mou Wang, Haohe Liu +11
Acoustic scene classification (ASC) is a crucial research problem in computational auditory scene analysis, and it aims to recognize the unique acoustic characteristics of an envir…
Sub-band and Full-band Interactive U-Net with DPRNN for Demixing Cross-talk Stereo Music
Han Yin, Mou Wang, Jisheng Bai +3
This paper presents a detailed description of our proposed methods for the ICASSP 2024 Cadenza Challenge. Experimental results show that the proposed system can achieve better perf…
Interactive Dual-Conformer with Scene-Inspired Mask for Soft Sound Event Detection
Han Yin, Jisheng Bai, Mou Wang +3
Traditional binary hard labels for sound event detection (SED) lack details about the complexity and variability of sound event distributions. Recently, a novel annotation workflow…
AudioLog: LLMs-Powered Long Audio Logging with Hybrid Token-Semantic Contrastive Learning
Jisheng Bai, Han Yin, Mou Wang +4
Previous studies in automated audio captioning have faced difficulties in accurately capturing the complete temporal details of acoustic scenes and events within long audio sequenc…