9 citations · 16 across the 9 of their papers we have counts for
10 papers
ECHOv2: A Frequency-Structured Pre-trained Acoustic Representation Model with Cross-Band Modeling for Machine Anomalous Sound Detection
Yucong Zhang, Juan Liu, Ming Li
Machine anomalous sound detection (ASD) is an important technology for industrial acoustic monitoring, where robust acoustic representation learning remains challenging due to limi…
Toward Multimodal Industrial Fault Analysis: A Single-Speed Chain Conveyor Dataset with Audio and Vibration Signals
Zhang Chen, Yucong Zhang, Xiaoxiao Miao +1
We introduce a multimodal industrial fault analysis dataset collected from a single-speed chain conveyor (SSCC) system, targeting system-level fault detection in production lines.…
Multi-scale Scanning Network for Machine Anomalous Sound Detection
Yucong Zhang, Juan Liu, Ming Li
Machine sounds exhibit consistent and repetitive patterns in both the frequency and time domains, which vary significantly across scales for different machine types. For instance,…
ECHO: Frequency-aware Hierarchical Encoding for Variable-length Signals
Yucong Zhang, Juan Liu, Ming Li
Pre-trained foundation models have demonstrated remarkable success in audio, vision and language, yet their potential for general machine signal modeling with arbitrary sampling ra…
A Dual-Path Framework with Frequency-and-Time Excited Network for Anomalous Sound Detection
Yucong Zhang, Juan Liu, Yao Tian +2
In contrast to human speech, machine-generated sounds of the same type often exhibit consistent frequency characteristics and discernible temporal periodicity. However, leveraging…
Multimodal Laryngoscopic Video Analysis for Assisted Diagnosis of Vocal Fold Paralysis
Yucong Zhang, Xin Zou, Jinshan Yang +4
This paper presents the Multimodal Laryngoscopic Video Analyzing System (MLVAS), a novel system that leverages both audio and video data to automatically extract key video segments…
Outlier-aware Inlier Modeling and Multi-scale Scoring for Anomalous Sound Detection via Multitask Learning
Yucong Zhang, Hongbin Suo, Yulong Wan +1
This paper proposes an approach for anomalous sound detection that incorporates outlier exposure and inlier modeling within a unified framework by multitask learning. While outlier…
The DKU-DukeECE Diarization System for the VoxCeleb Speaker Recognition Challenge 2022
Weiqing Wang, Xiaoyi Qin, Ming Cheng +3
This paper discribes the DKU-DukeECE submission to the 4th track of the VoxCeleb Speaker Recognition Challenge 2022 (VoxSRC-22). Our system contains a fused voice activity detectio…
Target-Speaker Voice Activity Detection via Sequence-to-Sequence Prediction
Ming Cheng, Weiqing Wang, Yucong Zhang +2
Target-speaker voice activity detection is currently a promising approach for speaker diarization in complex acoustic environments. This paper presents a novel Sequence-to-Sequence…
Low-Latency Online Speaker Diarization with Graph-Based Label Generation
Yucong Zhang, Qinjian Lin, Weiqing Wang +4
This paper introduces an online speaker diarization system that can handle long-time audio with low latency. We enable Agglomerative Hierarchy Clustering (AHC) to work in an online…