Zobrazeno 1 - 10
of 332
pro vyhledávání: '"Wang, Mou"'
Deep learning-based sound event localization and classification is an emerging research area within wireless acoustic sensor networks. However, current methods for sound event localization and classification typically rely on a single microphone arra
Externí odkaz:
http://arxiv.org/abs/2403.20130
Autor:
Bai, Jisheng, Wang, Mou, Liu, Haohe, Yin, Han, Jia, Yafei, Huang, Siwei, Du, Yutong, Zhang, Dongzhe, Shi, Dongyuan, Gan, Woon-Seng, Plumbley, Mark D., Rahardja, Susanto, Xiang, Bin, Chen, Jianfeng
Acoustic scene classification (ASC) is a crucial research problem in computational auditory scene analysis, and it aims to recognize the unique acoustic characteristics of an environment. One of the challenges of the ASC task is the domain shift betw
Externí odkaz:
http://arxiv.org/abs/2402.02694
Traditional binary hard labels for sound event detection (SED) lack details about the complexity and variability of sound event distributions. Recently, a novel annotation workflow is proposed to generate fine-grained non-binary soft labels, resultin
Externí odkaz:
http://arxiv.org/abs/2311.14068
Autor:
Bai, Jisheng, Yin, Han, Wang, Mou, Shi, Dongyuan, Gan, Woon-Seng, Chen, Jianfeng, Rahardja, Susanto
Previous studies in automated audio captioning have faced difficulties in accurately capturing the complete temporal details of acoustic scenes and events within long audio sequences. This paper presents AudioLog, a large language models (LLMs)-power
Externí odkaz:
http://arxiv.org/abs/2311.12371
3D speech enhancement can effectively improve the auditory experience and plays a crucial role in augmented reality technology. However, traditional convolutional-based speech enhancement methods have limitations in extracting dynamic voice informati
Externí odkaz:
http://arxiv.org/abs/2306.04987
This work focuses on 3D Radar imaging inverse problems. Current methods obtain undifferentiated results that suffer task-depended information retrieval loss and thus don't meet the task's specific demands well. For example, biased scattering energy m
Externí odkaz:
http://arxiv.org/abs/2211.14989
Anomalous sound detection for machine condition monitoring has great potential in the development of Industry 4.0. However, these anomalous sounds of machines are usually unavailable in normal conditions. Therefore, the models employed have to learn
Externí odkaz:
http://arxiv.org/abs/2208.03421
A Squeeze-and-Excitation and Transformer based Cross-task System for Environmental Sound Recognition
Environmental sound recognition (ESR) is an emerging research topic in audio pattern recognition. Many tasks are presented to resort to computational models for ESR in real-life applications. However, current models are usually designed for individua
Externí odkaz:
http://arxiv.org/abs/2203.08350
Publikováno v:
In Signal Processing: Image Communication August 2024 126
Autor:
Guo, Jingyu, Wang, Mou, Jiang, Gen, Cheng, Weiqi, Lin, Yubin, Wang, Kai, Cheng, Songbai, Tan, Shaojie, Zhou, Wenzhong
Publikováno v:
In Nuclear Engineering and Design October 2024 427