14 citations · 30 across the 19 of their papers we have counts for
19 papers
Physics-Aware Novel-View Acoustic Synthesis with Vision-Language Priors and 3D Acoustic Environment Modeling
Congyi Fan, Jian Guan, Youtian Lin +5
Spatial audio is essential for immersive experiences, yet novel-view acoustic synthesis (NVAS) remains challenging due to complex physical phenomena such as reflection, diffraction…
DualMark: Identifying Model and Training Data Origins in Generated Audio
Xuefeng Yang, Jian Guan, Feiyang Xiao +5
Existing watermarking methods for audio generative models only enable model-level attribution, allowing the identification of the originating generation model, but are unable to tr…
Attacking Voice Anonymization Systems with Augmented Feature and Speaker Identity Difference
Yanzhe Zhang, Zhonghao Bi, Feiyang Xiao +3
This study focuses on the First VoicePrivacy Attacker Challenge within the ICASSP 2025 Signal Processing Grand Challenge, which aims to develop speaker verification systems capable…
Disentangling Hierarchical Features for Anomalous Sound Detection Under Domain Shift
Jian Guan, Jiantong Tian, Qiaoxi Zhu +3
Anomalous sound detection (ASD) encounters difficulties with domain shift, where the sounds of machines in target domains differ significantly from those in source domains due to v…
Spectral-Temporal Fusion Representation for Person-in-Bed Detection
Xuefeng Yang, Shiheng Zhang, Jian Guan +3
This study is based on the ICASSP 2025 Signal Processing Grand Challenge's Accelerometer-Based Person-in-Bed Detection Challenge, which aims to determine bed occupancy using accele…
Graph-Enhanced Dual-Stream Feature Fusion with Pre-Trained Model for Acoustic Traffic Monitoring
Shitong Fan, Feiyang Xiao, Wenbo Wang +4
Microphone array techniques are widely used in sound source localization and smart city acoustic-based traffic monitoring, but these applications face significant challenges due to…
Independent Feature Enhanced Crossmodal Fusion for Match-Mismatch Classification of Speech Stimulus and EEG Response
Shitong Fan, Wenbo Wang, Feiyang Xiao +3
It is crucial for auditory attention decoding to classify matched and mismatched speech stimuli with corresponding EEG responses by exploring their relationship. However, existing…
A Reference-free Metric for Language-Queried Audio Source Separation using Contrastive Language-Audio Pretraining
Feiyang Xiao, Jian Guan, Qiaoxi Zhu +6
Language-queried audio source separation (LASS) aims to separate an audio source guided by a text query, with the signal-to-distortion ratio (SDR)-based metrics being commonly used…
Transformer-based Autoencoder with ID Constraint for Unsupervised Anomalous Sound Detection
Jian Guan, Youde Liu, Qiuqiang Kong +4
Unsupervised anomalous sound detection (ASD) aims to detect unknown anomalous sounds of devices when only normal sound data is available. The autoencoder (AE) and self-supervised l…
First-Shot Unsupervised Anomalous Sound Detection With Unknown Anomalies Estimated by Metadata-Assisted Audio Generation
Hejing Zhang, Qiaoxi Zhu, Jian Guan +6
First-shot (FS) unsupervised anomalous sound detection (ASD) is a brand-new task introduced in DCASE 2023 Challenge Task 2, where the anomalous sounds for the target machine types…
Synth-AC: Enhancing Audio Captioning with Synthetic Supervision
Feiyang Xiao, Qiaoxi Zhu, Jian Guan +4
Data-driven approaches hold promise for audio captioning. However, the development of audio captioning methods can be biased due to the limited availability and quality of text-aud…
Anomalous Sound Detection Using Self-Attention-Based Frequency Pattern Analysis of Machine Sounds
Hejing Zhang, Jian Guan, Qiaoxi Zhu +2
Different machines can exhibit diverse frequency patterns in their emitted sound. This feature has been recently explored in anomaly sound detection and reached state-of-the-art pe…
Hierarchical Metadata Information Constrained Self-Supervised Learning for Anomalous Sound Detection Under Domain Shift
Haiyan Lan, Qiaoxi Zhu, Jian Guan +2
Self-supervised learning methods have achieved promising performance for anomalous sound detection (ASD) under domain shift, where the type of domain shift is considered in feature…
Time-weighted Frequency Domain Audio Representation with GMM Estimator for Anomalous Sound Detection
Jian Guan, Youde Liu, Qiaoxi Zhu +3
Although deep learning is the mainstream method in unsupervised anomalous sound detection, Gaussian Mixture Model (GMM) with statistical audio frequency representation as input can…
Anomalous Sound Detection using Audio Representation with Machine ID based Contrastive Learning Pretraining
Jian Guan, Feiyang Xiao, Youde Liu +2
Existing contrastive learning methods for anomalous sound detection refine the audio representation of each audio sample by using the contrast between the samples' augmentations (e…
Graph Attention for Automated Audio Captioning
Feiyang Xiao, Jian Guan, Qiaoxi Zhu +1
State-of-the-art audio captioning methods typically use the encoder-decoder structure with pretrained audio neural networks (PANNs) as encoders for feature extraction. However, the…
Neural Sound Field Decomposition with Super-resolution of Sound Direction
Qiuqiang Kong, Shilei Liu, Junjie Shi +5
Sound field decomposition predicts waveforms in arbitrary directions using signals from a limited number of microphones as inputs. Sound field decomposition is fundamental to downs…
Anomalous Sound Detection using Spectral-Temporal Information Fusion
Youde Liu, Jian Guan, Qiaoxi Zhu +1
Unsupervised anomalous sound detection aims to detect unknown abnormal sounds of machines from normal sounds. However, the state-of-the-art approaches are not always stable and per…
Local Information Assisted Attention-free Decoder for Audio Captioning
Feiyang Xiao, Jian Guan, Haiyan Lan +2
Automated audio captioning aims to describe audio data with captions using natural language. Existing methods often employ an encoder-decoder structure, where the attention-based d…