Zobrazeno 1 - 10
of 1 709
pro vyhledávání: '"CHENG Ning"'
Publikováno v:
大数据, Vol 10, Pp 56-73 (2024)
As a significant research area in the field of speech technology, speech synthesis is dedicated to converting text into speech. With the rapid development of deep learning technology, the objective of speech synthesis has evolved beyond merely produc
Externí odkaz:
https://doaj.org/article/5168bf2f58b24493bef8fefb6f82d198
Publikováno v:
大数据, Vol 10, Pp 74-95 (2024)
In the interdisciplinary field of modern computer vision and natural language processing, digital talking facial generation technology has become an increasingly important research topic. Digital facial generation technology focuses on generating rea
Externí odkaz:
https://doaj.org/article/642caef5795641a486b14ac35dd88080
Autor:
Cheng Ning Loong, Chih-Chen Chang
Publikováno v:
Computers and Education: Artificial Intelligence, Vol 7, Iss , Pp 100292- (2024)
A student's learning system is a system that guides the student's knowledge acquisition process using available learning resources to produce certain learning outcomes that can be evaluated based on the scores of questions in an assessment. Such a le
Externí odkaz:
https://doaj.org/article/84f9cd2d95da45469f37d508abad1e2b
Autor:
Zhiyong Yang, Xu Liu, Cheng Ning, Lanlan Liu, Wang Tian, Haoyang Wang, Daode Zhang, Huaxu Li, Dehua Zou, Jianghua Kuang
Publikováno v:
Actuators, Vol 12, Iss 9, p 352 (2023)
To ensure the safe operation of high-voltage transmission line inspection robots during downhill descents without power and extend their range after a single charge, this paper proposes an energy-saving speed control method for the inspection robot
Externí odkaz:
https://doaj.org/article/baf0f94d153e40e58cd40bf21de91d05
This paper introduces a novel privacy-preservation framework named PFID for LLMs that addresses critical privacy concerns by localizing user data through model sharding and singular value decomposition. When users are interacting with LLM systems, th
Externí odkaz:
http://arxiv.org/abs/2406.12238
Autor:
Zhuang, Ziyang, Miao, Chenfeng, Zou, Kun, Fang, Ming, Wei, Tao, Li, Zijian, Cheng, Ning, Hu, Wei, Wang, Shaojun, Xiao, Jing
Non-autoregressive (NAR) automatic speech recognition (ASR) models predict tokens independently and simultaneously, bringing high inference speed. However, there is still a gap in the accuracy of the NAR models compared to the autoregressive (AR) mod
Externí odkaz:
http://arxiv.org/abs/2406.08835
Autor:
Cheng, Ning, Guan, Changhao, Gao, Jing, Wang, Weihao, Li, You, Meng, Fandong, Zhou, Jie, Fang, Bin, Xu, Jinan, Han, Wenjuan
Touch holds a pivotal position in enhancing the perceptual and interactive capabilities of both humans and robots. Despite its significance, current tactile research mainly focuses on visual and tactile modalities, overlooking the language domain. In
Externí odkaz:
http://arxiv.org/abs/2406.03813
Publikováno v:
IEEE Access, Vol 8, Pp 89617-89629 (2020)
Due to their simplicity and flexibility, the unsupervised statistical models such as Gaussian mixture model (GMM) are powerful tools to address the brain magnetic resonance (MR) images segmentation problems. However, the GMM is based only on the inte
Externí odkaz:
https://doaj.org/article/b706d51eb9de4b16ab92b73e6bd42255
Publikováno v:
中西医结合护理, Vol 7, Iss 1, Pp 123-125 (2021)
This paper summarized the Traditional Chinese Medicine (TCM) nursing management of a case with severe allergic dermatitis induced by rabies vaccine. Individualized nursing interventions were carried out including TCM Tazi treatment, TCM inunction, au
Externí odkaz:
https://doaj.org/article/355e67a2809b4e8eb42ebddba73240fa
The purpose of emotion recognition in conversation (ERC) is to identify the emotion category of an utterance based on contextual information. Previous ERC methods relied on simple connections for cross-modal fusion and ignored the information differe
Externí odkaz:
http://arxiv.org/abs/2405.17900