检索结果-内蒙古大学图书馆

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Yajie Liu Xinmeng Xu Weiping Tu Yuhong Yang Li Xiao School of Computer Science National Engineering Research Center for Multimedia Software Wuhan University China Hubei Key Laboratory of Multimedia and Network Communication Engineering Wuhan University China

We propose MiT-Net, a novel mix-transformer neural network with a pyramid encoder operating in the time domain, for the task of acoustic echo cancellation. The MiT-Net formulates acoustic echo cancellation as a supervised speech separation problem, in which near-end speech is separated from a single microphone recording and sent to the far end, and consists of two key components. First, we apply a pyramid encoder, which adopts the coarse-to-fine structure, to extract the latent correlations between double-end signals and to fuse them in a multiscale manner. Second, we propose a mix-transformer, a combination of local and global attention in a parallel way, to leverage local and global speech information for separation. Experimental results show that the proposed method outperforms recent AEC methods in terms of objective evaluation metrics. In addition, exploring the correlation between speech local and global features by using the mix-transformer significantly improves the system performance and shows more robustness than the conventional transformer.

关键词： Echo cancellers Correlation Fuses System performance Transformers Feature extraction Acoustics

来源：评论

学校读者我要写书评

暂无评论

CRPWarner: Warning the Risk of Contract-related Rug Pull in DeFi Smart Contracts

arXiv

引用

arXiv 2024年

作者： Lin, Zewei Chen, Jiachi Zheng, Zibin Wu, Jiajing Zhang, Weizhe Wang, Yongjuan School of Software Engineering Sun Yat-sen University China School of Computer Science and Technology Harbin Institute of Technology China Henan Key Laboratory of Network Cryptography Technology China

In recent years, Decentralized Finance (DeFi) grows rapidly due to the development of blockchain technology and smart contracts. As of March 2023, the estimated global cryptocurrency market cap has reached approximately $949 billion. However, security incidents continue to plague the DeFi ecosystem, and one of the most notorious examples is the "Rug Pull" scam. This type of cryptocurrency scam occurs when the developer of a particular token project intentionally abandons the project and disappears with investors’ funds. Despite it only emerging in recent years, Rug Pull events have already caused significant financial losses. In this work, we manually collected and analyzed 103 real-world rug pull events, categorizing them based on their scam methods. Two primary categories were identified: Contract-related Rug Pull (through malicious functions in smart contracts) and Transaction-related Rug Pull (through cryptocurrency trading without utilizing malicious functions). Based on the analysis of rug pull events, we propose CRPWarner (short for Contract-related Rug Pull Risk Warner) to identify malicious functions in smart contracts and issue warnings regarding potential rug pulls. We evaluated CRPWarner on 69 open-source smart contracts related to rug pull events and achieved a 91.8% precision, 85.9% recall and 88.7% F1-score. Additionally, when evaluating CRPWarner on 13,484 real token contracts on Ethereum, it successfully detected 4168 smart contracts with malicious functions, including zero-day examples. The precision of large-scale experiment reach 84.9%. Copyright © 2024, The Authors. All rights reserved.

关键词： Smart contract

来源：评论

学校读者我要写书评

暂无评论

FISHFUZZ: catch deeper bugs by throwing larger nets 23

FISHFUZZ: catch deeper bugs by throwing larger nets

引用

Proceedings of the 32nd USENIX Conference on Security Symposium

作者： Han Zheng Jiayuan Zhang Yuhang Huang Zezhong Ren He Wang Chunjie Cao Yuqing Zhang Flavio Toffalini Mathias Payer National Computer Network Intrusion Protection Center University of Chinese Academy of Science and School of Computer and Communication Sciences EPFL National Computer Network Intrusion Protection Center University of Chinese Academy of Science and School of Computer and Communication Lanzhou University of Technology National Computer Network Intrusion Protection Center University of Chinese Academy of Science National Computer Network Intrusion Protection Center University of Chinese Academy of Science and Zhongguancun Laboratory School of Cyber Engineering Xidian University School of Cyberspace Security Hainan University National Computer Network Intrusion Protection Center University of Chinese Academy of Science and Zhongguancun Laboratory and School of Cyberspace Security Hainan University and School of Cyber Engineering Xidian University School of Computer and Communication Sciences EPFL

ISBN: (纸本)9781939133373

Fuzzers effectively explore programs to discover bugs. Greybox fuzzers mutate seed inputs and observe their execution. Whenever a seed reaches new behavior (e.g., new code or higher execution frequency), it is stored for further mutation. Greybox fuzzers directly measure exploration and, by repeating execution of the same targets with large amounts of mutated seeds, passively exploit any lingering bugs. Directed greybox fuzzers (DGFs) narrow the search to a few code locations but so far generalize distance to all targets into a single score and do not prioritize targets *** introduces an input prioritization strategy that builds on three concepts: (i) a novel multi-distance metric whose precision is independent of the number of targets, (ii) a dynamic target ranking to automatically discard exhausted targets, and (iii) a smart queue culling algorithm, based on hyperparameters, that alternates between exploration and exploitation. FISHFUZZ enables fuzzers to seamlessly scale among thousands of targets and prioritize seeds toward interesting locations, thus achieving more comprehensive program testing. To demonstrate generality, we implement FISHFUZZ over two well-established greybox fuzzers (AFL and AFL++). We evaluate FISHFUZZ by leveraging all sanitizer labels as targets. In comparison to modern DGFs and state-of-the-art coverage guided fuzzers, FISHFUZZ reaches higher coverage compared to the direct competitors, finds up to 2.8x more bugs compared with the baseline and reproduces 68.3% existing bugs faster. FISHFUZZ also discovers 56 new bugs (38 CVEs) in 47 programs.

关键词：

来源：评论

学校读者我要写书评

暂无评论

HAPG-SAQAM: Human Auditory Perception Guided Spatial Audio Quality Assessment Metric

HAPG-SAQAM: Human Auditory Perception Guided Spatial Audio Q...

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Yuanming Zheng Jiaxuan Yao Xiangyu Deng Yuhong Yang Ruiqi Liao Weiping Tu Cedar Lin National Engineering Research Center for Multimedia Software School of Computer Science Wuhan University Wuhan China Hubei Key Laboratory of Multimedia and Network Communication Engineering Wuhan China Guangdong OPPO Mobile Telecommunications Corp. China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Spatial audio quality evaluation is essential for applications like virtual and augmented reality, where accurate sound reproduction enhances user immersion. While subjective listening tests are the gold standard, they are costly and time-consuming. To address this, we propose HAPG-SAQAM, an objective metric for assessing timbre quality, spatial quality, and overall quality of binaural audio, guided by human auditory perception. Our contributions include: (1) the Multi-scale Auditory Guided Feature Extraction (MAGFE) module, incorporating gammatone frequency cepstral coefficients for better alignment with human perception; (2) Perceptual Weighted Loss (PWL), optimizing the weighting of timbre quality (TQ) and spatial quality (SQ) loss based on subjective test data; and (3) data augmentation techniques to enhance robustness by amplifying perceptual distortions. Experimental results show HAPG-SAQAM improves correlation with subjective scores by 10%, with ablation studies confirming the contributions of its components to enhanced spatial and overall audio quality.

关键词： Measurement Accuracy Spatial audio Performance gain Feature extraction Robustness Quality assessment Timbre Speech processing Optimization

来源：评论

学校读者我要写书评

暂无评论

A news image captioning approach based on multimodal pointer-generator network

A news image captioning approach based on multimodal pointer...

引用

作者： Chen, Jingqiang Zhuge, Hai School of Computer Science Nanjing University of Posts and Telecommunications Nanjing China School of Computer Science and Network Engineering Guangzhou University Guangzhou China Department of Computer Science School of Engineering and Applied Science Aston University Birmingham United Kingdom Key Laboratory of Intelligent Information Processing Institute of Computing Technology University of Chinese Academy of Sciences Chinese Academy of Sciences Beijing China

News image captioning aims to generate captions or descriptions for news images automatically, serving as draft captions for creating news image captions manually. News image captions are different from generic captions as news image captions contain more detailed information such as entity names and events. Therefore, both images on news and the accompanying text are the source of generating caption of news image. Pointer-generator network is a neural method defined for text summarization. This article proposes the Multimodal pointer-generation network by incorporating visual information into the original network for news image captioning. The multimodal attention mechanism is proposed by splitting attention into visual attention paid to the image and textual attention paid to the text. The multimodal pointer mechanism is proposed by using both textual attention and visual attention to compute pointer distributions, where visual attention is first transformed into textual attention via the word-image relationships. The multimodal coverage mechanism is defined to reduce repetitions of attentions or repetitions of pointer distributions. Experiments on the DailyMail test dataset and the out-of-domain BBC test dataset show that the proposed model outperforms the original pointer-generator network, the generic image captioning method, the extractive news image captioning method, and the LDA-based method according BLEU, METEOR, and ROUGL-L evaluations. Experiments also show that the proposed multimodal coverage mechanisms can improve the model, and that transforming visual attention to pointer distributions can improve the model. © 2020 John Wiley & Sons, Ltd.

关键词： Statistical tests

来源：评论

学校读者我要写书评

暂无评论

CroPrompt: Cross-task Interactive Prompting for Zero-shot Spoken Language Understanding

CroPrompt: Cross-task Interactive Prompting for Zero-shot Sp...

引用

2025 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2025

作者： Qin, Libo Wei, Fuxuan Chen, Qiguang Zhou, Jingxuan Huang, Shijue Si, Jiasheng Lu, Wenpeng Che, Wanxiang School of Computer Science and Engineering Central South University China Key Laboratory of Data Intelligence and Advanced Computing in Provincial Universities Soochow University China Research Center for Social Computing and Information Retrieval Harbin Institute of Technology China Harbin Institute of Technology Shenzhen China Key Laboratory of Computing Power Network and Information Security Ministry of Education Qilu University of Technology Shandong Academy of Sciences China

ISBN: (纸本)9798350368741

Slot filling and intent detection are two highly correlated tasks in spoken language understanding (SLU). Recent SLU research attempts to explore zero-shot prompting techniques in large language models to alleviate the data scarcity problem. Nevertheless, the existing prompting work ignores the cross-task interaction information for SLU, which leads to sub-optimal performance. To solve this problem, we present the pioneering work of Cross-task Interactive Prompting (CroPrompt) for SLU, which enables the model to interactively leverage the information exchange across the correlated tasks in SLU. Additionally, we further introduce a multi-task self-consistency mechanism to mitigate the error propagation caused by the intent information injection. We conduct extensive experiments on the standard SLU benchmark and the results reveal that CroPrompt consistently outperforms the existing prompting approaches. In addition, the multi-task self-consistency mechanism can effectively ease the error propagation issue, thereby enhancing the performance. We hope this work can inspire more research on cross-task prompting for SLU. © 2025 IEEE.

关键词：

来源：评论

学校读者我要写书评

暂无评论

3-D Near-Field Localization by Jointly Exploiting Spatial and Temporal Information Based on a Nonuniform Cross Array

3-D Near-Field Localization by Jointly Exploiting Spatial an...

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Zelong Yi Hua Chen Zhiwei Jiang Wei Liu Qing Wang Gang Wang Faculty of Electrical Engineering and Computer Science Ningbo University Ningbo China Zhejiang Key Laboratory of Mobile Network Application Technology Ningbo China School of Electronic Engineering and Computer Science Queen Mary University of London London UK School of Electronic Informatin Engineering Tianjin University Tianjin China

In this paper, an underdetermined three-dimensional (3-D) near-field source localization method is proposed, based on a two-dimensional (2-D) symmetric nonuniform cross array. Firstly, the fourth-order cumulant of the near-field observations with multiple delay lags is exploited to construct virtual far-field pseudo-observations, leading to increased degrees of freedom (DOF); then, 2-D angles of the nearfield sources are jointly estimated by employing the recently proposed sparse and parametric approach (SPA) and Vandermonde decomposition technique, eliminating the need for parameter discretization. To estimate the range term, the one-dimensional (1-D) MUSIC algorithm is applied by resorting to the conjugate symmetry property of the signal's autocorrelation function. Numerical results are provided to demonstrate the superiority of our method.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Multi-speaker Direction of Arrival Estimation Using Audio and Visual Modalities with Convolutional Neural network

Multi-speaker Direction of Arrival Estimation Using Audio an...

引用

IEEE International Conference on Multimedia and Expo (ICME)

作者： Yulin Wu Ruimin Hu Xiaochen Wang National Engineering Research Center for Multimedia Software School of Computer Science Wuhan University Hubei Key Laboratory of Multimedia and Network Communication Engineering Wuhan University Wuhan China

In reality, audible and visible sound sources are closely aligned, and they can help humans locate sources exactly. To exploit the complementarity between audio and visual data in multi-speaker direction of arrival (DoA) estimation, we propose a novel network consisting of 3D convolution neural networks (3D-CNNs) and 2D-CNNs mixture networks with residual dense blocks. It has two main advantages: 1) both input audio and visual features are low-level signal representation: the real and imaginary parts of STFT coefficients for the audio feature and pixel coordinates for the visual feature, which can allow the network to learn to extract the most informative high-level features. 2) 3D-CNNs with the residual dense block are used for audio and visual feature mapping along the time and frequency axis. The following 2D-CNNs are to ensemble the high-level features along the DoA axis. Experimental results demonstrate promising SSL performance.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Hierarchical Prior-based Super Resolution for Point Cloud Geometry Compression

arXiv

引用

arXiv 2024年

作者： Li, Dingquan Ma, Kede Wang, Jing Li, Ge Network Intelligence Research Department Peng Cheng Laboratory Shenzhen China Department of Computer Science City University of Hong Kong Hong Kong School of Electronic and Computer Engineering Peking University Shenzhen Graduate School Shenzhen China

The Geometry-based Point Cloud Compression (GPCC) has been developed by the Moving Picture Experts Group to compress point clouds. In its lossy mode, the reconstructed point cloud by G-PCC often suffers from noticeable distortions due to the naive geometry quantization (i.e., grid downsampling). This paper proposes a hierarchical prior-based super resolution method for point cloud geometry compression. The contentdependent hierarchical prior is constructed at the encoder side, which enables coarse-to-fine super resolution of the point cloud geometry at the decoder side. A more accurate prior generally yields improved reconstruction performance, at the cost of increased bits required to encode this side information. With a proper balance between prior accuracy and bit consumption, the proposed method demonstrates substantial Bjontegaard-delta bitrate savings on the MPEG Cat1A dataset, surpassing the octree-based and trisoup-based G-PCC v14. We provide our implementations for reproducible research at https://***/ lidq92/mpeg-pcc-tmc13. © 2024, CC BY.

关键词： Geometry

来源：评论

学校读者我要写书评

暂无评论

High-quality Arabidopsis thaliana Genome Assembly with Nanopore and HiFi Long Reads

引用

Genomics, Proteomics & Bioinformatics 2022年第1期20卷 4-13页

作者： Bo Wang Xiaofei Yang Yanyan Jia Yu Xu Peng Jia Ningxin Dang Songbo Wang Tun Xu Xixi Zhao Shenghan Gao Quanbin Dong Kai Ye MOE Key Laboratory for Intelligent Networks&Network Security Faculty of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’an 710049China School of Computer Science and Technology Faculty of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’an 710049China School of Life Science and Technology Xi’an Jiaotong UniversityXi’an 710049China School of Automation Science and Engineering Faculty of Electronic and Information EngineeringXi’an Jiaotong UniversityXi’an 710049China Genome Institute the First Affiliated Hospital of Xi’an Jiaotong UniversityXi’an 710061China

Arabidopsis thaliana is an important and long-established model species for plant molecular biology,genetics,epigenetics,and ***,the latest version of reference genome still contains a significant number of missing ***,we reported a high-quality and almost complete Col-0 genome assembly with two gaps(named Col-XJTU)by combining the Oxford Nanopore Technologies ultra-long reads,Pacific Biosciences high-fidelity long reads,and Hi-C *** total genome assembly size is 133,725,193 bp,introducing 14.6 Mb of novel sequences compared to the TAIR10.1 reference *** five chromosomes of the Col-XJTU assembly are highly accurate with consensus quality(QV)scores>60(ranging from 62 to 68),which are higher than those of the TAIR10.1 reference(ranging from 45 to 52).We completely resolved chromosome(Chr)3 and Chr5 in a telomere-to-telomere ***4 was completely resolved except the nucleolar organizing regions,which comprise long repetitive DNA *** Chrl centromere(CEN1),reportedly around 9 Mb in length,is particularly challenging to assemble due to the presence of tens of thousands of CEN180 satellite *** the cutting-edge sequencing data and novel computational approaches,we assembled a 3.8-Mb-long CEN1 and a 3.5-Mb-long *** also investigated the structure and epigenetics of *** clusters of CEN180 monomers were detected,and the centromere-specific histone H3-like protein(CENH3)exhibited a strong preference for CEN180 Cluster ***,we observed hypomethylation patterns in CENH3-enriched *** believe that this high-quality genome assembly,Col-XJTU,would serve as a valuable reference to better understand the global pattern of centromeric polymorphisms,as well as the genetic and epigenetic features in plants.

关键词： Centromere architecture CENH3 Bacterial artificial chromosome Telomere-to-telomere Model plant

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：