1 citations · 1 across the 3 of their papers we have counts for
6 papers
ECHOv2: Two-Level Band-Splitting Representation Learning for Anomalous Sound Detection
Yucong Zhang, Juan Liu, Ming Li
Machine anomalous sound detection (ASD) requires robust audio representations capable of capturing subtle deviations in machine sounds under limited supervision. Existing pre-train…
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.…
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…
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…
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,…
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…