Zobrazeno 1 - 10
of 4 572
pro vyhledávání: '"REN Yong"'
Autor:
Xu, Jingzehua, Xie, Guanwen, Zhang, Ziqi, Hou, Xiangwang, Ma, Dongfang, Zhang, Shuai, Ren, Yong, Niyato, Dusit
Publikováno v:
IEEE Transactions on Mobile Computing 2024
It is significant to employ multiple autonomous underwater vehicles (AUVs) to execute the underwater target tracking task collaboratively. However, it's pretty challenging to meet various prerequisites utilizing traditional control methods. Therefore
Externí odkaz:
http://arxiv.org/abs/2412.03959
Autor:
Yan, Xinrui, Yi, Jiangyan, Tao, Jianhua, Chen, Yujie, Gu, Hao, Li, Guanjun, Zhou, Junzuo, Ren, Yong, Xu, Tao
Open environment oriented open set model attribution of deepfake audio is an emerging research topic, aiming to identify the generation models of deepfake audio. Most previous work requires manually setting a rejection threshold for unknown classes t
Externí odkaz:
http://arxiv.org/abs/2412.01425
In recent years, Large Language Models (LLMs) have demonstrated remarkable versatility across various applications, including natural language understanding, domain-specific knowledge tasks, etc. However, applying LLMs to complex, high-stakes domains
Externí odkaz:
http://arxiv.org/abs/2411.06852
Autor:
Elsie Kim Hiok Lim, Gordon Jian Ting Loh, Ren Yong Ong, Rachel Ruizhen Tan, Clement Chee Kin Yan, Katherin Shilin Huang, Melissa Yi Ching Chan, Meredith Tsz Ling Yeung
Publikováno v:
Proceedings of Singapore Healthcare, Vol 31 (2022)
Background Empathy is an essential antecedent in motivating healthcare professionals to treat and care for their patients with compassion – few studies had explored empathy on healthcare workers. Currently, no data reported empathy amongst physioth
Externí odkaz:
https://doaj.org/article/4aa22c60288648b8a5b48d5a4a6fc06b
Recent advances in speech spoofing necessitate stronger verification mechanisms in neural speech codecs to ensure authenticity. Current methods embed numerical watermarks before compression and extract them from reconstructed speech for verification,
Externí odkaz:
http://arxiv.org/abs/2409.12121
We introduce Diffusion-based Audio Captioning (DAC), a non-autoregressive diffusion model tailored for diverse and efficient audio captioning. Although existing captioning models relying on language backbones have achieved remarkable success in vario
Externí odkaz:
http://arxiv.org/abs/2409.09401
Visual and auditory perception are two crucial ways humans experience the world. Text-to-video generation has made remarkable progress over the past year, but the absence of harmonious audio in generated video limits its broader applications. In this
Externí odkaz:
http://arxiv.org/abs/2409.08601
Autor:
Gu, Hao, Yi, JiangYan, Wang, Chenglong, Ren, Yong, Tao, Jianhua, Yan, Xinrui, Chen, Yujie, Zhang, Xiaohui
Fake audio detection is an emerging active topic. A growing number of literatures have aimed to detect fake utterance, which are mostly generated by Text-to-speech (TTS) or voice conversion (VC). However, countermeasures against impersonation remain
Externí odkaz:
http://arxiv.org/abs/2408.17009
Autor:
Yi, Jiangyan, Zhang, Chu Yuan, Tao, Jianhua, Wang, Chenglong, Yan, Xinrui, Ren, Yong, Gu, Hao, Zhou, Junzuo
The growing prominence of the field of audio deepfake detection is driven by its wide range of applications, notably in protecting the public from potential fraud and other malicious activities, prompting the need for greater attention and research i
Externí odkaz:
http://arxiv.org/abs/2408.04967