7 citations · 9 across the 6 of their papers we have counts for
6 papers
Towards Fine-grained Temporal Perception: Post-Training Large Audio-Language Models with Audio-Side Time Prompt
Yanfeng Shi, Pengfei Cai, Jun Liu +5
Large Audio-Language Models (LALMs) enable general audio understanding and demonstrate remarkable performance across various audio tasks. However, these models still face challenge…
Spectrogram features for audio and speech analysis
Ian McLoughlin, Lam Pham, Yan Song +7
Spectrogram-based representations have grown to dominate the feature space for deep learning audio analysis systems, and are often adopted for speech analysis also. Initially, the…
Detect Any Sound: Open-Vocabulary Sound Event Detection with Multi-Modal Queries
Pengfei Cai, Yan Song, Qing Gu +3
Most existing sound event detection~(SED) algorithms operate under a closed-set assumption, restricting their detection capabilities to predefined classes. While recent efforts hav…
Prototype based Masked Audio Model for Self-Supervised Learning of Sound Event Detection
Pengfei Cai, Yan Song, Nan Jiang +2
A significant challenge in sound event detection (SED) is the effective utilization of unlabeled data, given the limited availability of labeled data due to high annotation costs.…
USTC-KXDIGIT System Description for ASVspoof5 Challenge
Yihao Chen, Haochen Wu, Nan Jiang +13
This paper describes the USTC-KXDIGIT system submitted to the ASVspoof5 Challenge for Track 1 (speech deepfake detection) and Track 2 (spoofing-robust automatic speaker verificatio…
MAT-SED: A Masked Audio Transformer with Masked-Reconstruction Based Pre-training for Sound Event Detection
Pengfei Cai, Yan Song, Kang Li +2
Sound event detection (SED) methods that leverage a large pre-trained Transformer encoder network have shown promising performance in recent DCASE challenges. However, they still r…