Zobrazeno 1 - 10
of 463
pro vyhledávání: '"Mcloughlin, Ian"'
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. Semi-supervised algorithms rely on labeled data to learn from unlabele
Externí odkaz:
http://arxiv.org/abs/2409.17656
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 rely on an RNN-based context network to model temporal dependencies, la
Externí odkaz:
http://arxiv.org/abs/2408.08673
Autor:
Miao, Xiaoxiao, Zhang, Yuxiang, Wang, Xin, Tomashenko, Natalia, Soh, Donny Cheng Lock, Mcloughlin, Ian
A general disentanglement-based speaker anonymization system typically separates speech into content, speaker, and prosody features using individual encoders. This paper explores how to adapt such a system when a new speech attribute, for example, em
Externí odkaz:
http://arxiv.org/abs/2408.05928
Autor:
Zeng, Xiao-Min, Song, Yan, Zhuo, Zhu, Zhou, Yu, Li, Yu-Hong, Xue, Hui, Dai, Li-Rong, McLoughlin, Ian
In this paper, we propose a joint generative and contrastive representation learning method (GeCo) for anomalous sound detection (ASD). GeCo exploits a Predictive AutoEncoder (PAE) equipped with self-attention as a generative model to perform frame-l
Externí odkaz:
http://arxiv.org/abs/2305.12111
In this paper, we propose an effective sound event detection (SED) method based on the audio spectrogram transformer (AST) model, pretrained on the large-scale AudioSet for audio tagging (AT) task, termed AST-SED. Pretrained AST models have recently
Externí odkaz:
http://arxiv.org/abs/2303.03689
Autor:
Pham, Lam, Le, Cam, Ngo, Dat, Nguyen, Anh, Lampert, Jasmin, Schindler, Alexander, McLoughlin, Ian
In this paper, we present a high-performance and light-weight deep learning model for Remote Sensing Image Classification (RSIC), the task of identifying the aerial scene of a remote sensing image. To this end, we first valuate various benchmark conv
Externí odkaz:
http://arxiv.org/abs/2302.13028