Search

Your search keyword '"Liu, Chenglin"' showing total 1,378 results
Start Over Author "Liu, Chenglin"
1,378 results on '"Liu, Chenglin"'

1. From Statistical Methods to Pre-Trained Models; A Survey on Automatic Speech Recognition for Resource Scarce Urdu Language

Author

Sharif, Muhammad, Abbas, Zeeshan, Yi, Jiangyan, and Liu, Chenglin

Subjects
Computer Science - Computation and Language, Computer Science - Sound, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

Automatic Speech Recognition (ASR) technology has witnessed significant advancements in recent years, revolutionizing human-computer interactions. While major languages have benefited from these developments, lesser-resourced languages like Urdu face unique challenges. This paper provides an extensive exploration of the dynamic landscape of ASR research, focusing particularly on the resource-constrained Urdu language, which is widely spoken across South Asian nations. It outlines current research trends, technological advancements, and potential directions for future studies in Urdu ASR, aiming to pave the way for forthcoming researchers interested in this domain. By leveraging contemporary technologies, analyzing existing datasets, and evaluating effective algorithms and tools, the paper seeks to shed light on the unique challenges and opportunities associated with Urdu language processing and its integration into the broader field of speech research., Comment: Submitted to SN Computer Science

Published
2024

2. GeoEval: Benchmark for Evaluating LLMs and Multi-Modal Models on Geometry Problem-Solving

Author

Zhang, Jiaxin, Li, Zhongzhi, Zhang, Mingliang, Yin, Fei, Liu, Chenglin, and Moshfeghi, Yashar

Subjects
Computer Science - Artificial Intelligence, Computer Science - Computation and Language
Abstract

Recent advancements in large language models (LLMs) and multi-modal models (MMs) have demonstrated their remarkable capabilities in problem-solving. Yet, their proficiency in tackling geometry math problems, which necessitates an integrated understanding of both textual and visual information, has not been thoroughly evaluated. To address this gap, we introduce the GeoEval benchmark, a comprehensive collection that includes a main subset of 2,000 problems, a 750 problems subset focusing on backward reasoning, an augmented subset of 2,000 problems, and a hard subset of 300 problems. This benchmark facilitates a deeper investigation into the performance of LLMs and MMs in solving geometry math problems. Our evaluation of ten LLMs and MMs across these varied subsets reveals that the WizardMath model excels, achieving a 55.67\% accuracy rate on the main subset but only a 6.00\% accuracy on the hard subset. This highlights the critical need for testing models against datasets on which they have not been pre-trained. Additionally, our findings indicate that GPT-series models perform more effectively on problems they have rephrased, suggesting a promising method for enhancing model capabilities., Comment: Accepted in ACL 2024 Findings

Published
2024

11. Unmanned Aerial Vehicle Path Planning Algorithm Based on Improved Informed RRT* in Complex Environment

Author

LIU Wenqian, SHAN Liang, ZHANG Weilong, LIU Chenglin, MA Qiang

Subjects
path planning, informed rrt* (irrt*), artificial potential field (apf) method, adaptive step size, elliptic sampling domain, Engineering (General). Civil engineering (General), TA1-2040, Chemical engineering, TP155-156, Naval architecture. Shipbuilding. Marine engineering, VM1-989
Abstract

To address the problems of long planning time, redundant planning path, and even planning failure caused by local constraints in narrow spaces in the rapid exploring random trees (RRT) algorithm when unmanned aerial vehicle is planning a path in a complex environment, an improved Informed RRT* algorithm is proposed. First, the artificial potential field (APF) method is used to make the sampling points move to the target point in the way of potential field descending, which improves the purpose and directionality of RRT tree expansion. Considering the complexity of the global environment during tree expansion, an adaptive step size is introduced to accelerate the expansion speed of the RRT tree in an unobstructed environment. Then, relevant constraints are added in the process of random tree expansion to ensure the feasibility of the generated paths. After the first reachable path is found, variable elliptic or ellipsoidal sampling domain is used to limit the selection of sampling points and the expansion range of adaptive step size, so as to accelerate the convergence of the algorithm to the asymptotic optimization. Finally, the original algorithm and the improved algorithm are compared in two-dimensional and three-dimensional complex environment. The simulation results show that the improved algorithm can find a better reachable path with a small number of iterations, lock the elliptic or ellipsoidal sampling domain faster and leave more time for path optimization. The improved algorithm performs better in path planning.

Published
2024
Full Text
View/download PDF

31. Nonsingular Fast Terminal Sliding Mode Control of Stewart Parallel Robot

Author

Wang, Xiaoyue, Liu, Chenglin, Angrisani, Leopoldo, Series Editor, Arteaga, Marco, Series Editor, Chakraborty, Samarjit, Series Editor, Chen, Jiming, Series Editor, Chen, Shanben, Series Editor, Chen, Tan Kay, Series Editor, Dillmann, Rüdiger, Series Editor, Duan, Haibin, Series Editor, Ferrari, Gianluigi, Series Editor, Ferre, Manuel, Series Editor, Jabbari, Faryar, Series Editor, Jia, Limin, Series Editor, Kacprzyk, Janusz, Series Editor, Khamis, Alaa, Series Editor, Kroeger, Torsten, Series Editor, Li, Yong, Series Editor, Liang, Qilian, Series Editor, Martín, Ferran, Series Editor, Ming, Tan Cher, Series Editor, Minker, Wolfgang, Series Editor, Misra, Pradeep, Series Editor, Mukhopadhyay, Subhas, Series Editor, Ning, Cun-Zheng, Series Editor, Nishida, Toyoaki, Series Editor, Oneto, Luca, Series Editor, Panigrahi, Bijaya Ketan, Series Editor, Pascucci, Federica, Series Editor, Qin, Yong, Series Editor, Seng, Gan Woon, Series Editor, Speidel, Joachim, Series Editor, Veiga, Germano, Series Editor, Wu, Haitao, Series Editor, Zamboni, Walter, Series Editor, Zhang, Junjie James, Series Editor, Tan, Kay Chen, Series Editor, Jia, Yingmin, editor, Zhang, Weicun, editor, Fu, Yongling, editor, and Wang, Jiqiang, editor

Published
2023
Full Text
View/download PDF

47. Research and Improvement on Detection Algorithm of SCMA System

Author

Liu, Chenglin, Su, Yanyong, Liu, Ruiran, Qin, Zhongshuai, Akan, Ozgur, Editorial Board Member, Bellavista, Paolo, Editorial Board Member, Cao, Jiannong, Editorial Board Member, Coulson, Geoffrey, Editorial Board Member, Dressler, Falko, Editorial Board Member, Ferrari, Domenico, Editorial Board Member, Gerla, Mario, Editorial Board Member, Kobayashi, Hisashi, Editorial Board Member, Palazzo, Sergio, Editorial Board Member, Sahni, Sartaj, Editorial Board Member, Shen, Xuemin, Editorial Board Member, Stan, Mircea, Editorial Board Member, Jia, Xiaohua, Editorial Board Member, Zomaya, Albert Y., Editorial Board Member, Wu, Kaishun, editor, Wang, Lu, editor, and Chen, Yanjiao, editor

Published
2022
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results