activity
20212025
most citedGraph Attention for Automated Audio Captioning

14 citations · 32 across the 15 of their papers we have counts for

collaborators

15 papers

cs.SD2025

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…

eess.AS2025

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…

cs.SD2025

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…

eess.SP2024

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…

eess.AS2024

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…

eess.AS2024

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…

cs.SD2024

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…

cs.SD2023

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…

cs.SD2023

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…

cs.SD2023★ 1 cited

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…

cs.SD2023

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…

cs.SD2023

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…

cs.SD2023★ 14 cited

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…

cs.SD2022★ 13 cited

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…

cs.SD2021★ 4 cited

Time-domain Speech Enhancement with Generative Adversarial Learning

Feiyang Xiao, Jian Guan, Qiuqiang Kong +1

Speech enhancement aims to obtain speech signals with high intelligibility and quality from noisy speech. Recent work has demonstrated the excellent performance of time-domain deep…