ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)最新文献_第6页

Robust Fir Filters for Wireless Low-Frequency Sound Zones 用于无线低频声区的鲁棒Fir滤波器

ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2023-06-04 DOI: 10.1109/ICASSP49357.2023.10095256

Mo Zhou, M. Møller, Christian Pedersen, Jan Østergaard

引用次数: 0

CSM In Motion Vector Steganalysis: The Effect of Coders on Motion Vectors in H.264 Video Encoding 运动矢量隐写分析中的CSM: H.264视频编码中编码器对运动矢量的影响

ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2023-06-04 DOI: 10.1109/ICASSP49357.2023.10096323

Verena Lachner, K. Schaar, Ralf Zimmermann

引用次数: 0

Outside Knowledge Visual Question Answering Version 2.0 外部知识可视化问答2.0版

ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2023-06-04 DOI: 10.1109/ICASSP49357.2023.10096074

Benjamin Z. Reichman, Anirudh S. Sundar, Christopher Richardson, Tamara Zubatiy, Prithwijit Chowdhury, Aaryan Shah, Jack Truxal, Micah Grimes, Dristi Shah, Woo Ju Chee, Saif Punjwani, Atishay Jain, L. Heck

{"title":"Outside Knowledge Visual Question Answering Version 2.0","authors":"Benjamin Z. Reichman, Anirudh S. Sundar, Christopher Richardson, Tamara Zubatiy, Prithwijit Chowdhury, Aaryan Shah, Jack Truxal, Micah Grimes, Dristi Shah, Woo Ju Chee, Saif Punjwani, Atishay Jain, L. Heck","doi":"10.1109/ICASSP49357.2023.10096074","DOIUrl":"https://doi.org/10.1109/ICASSP49357.2023.10096074","url":null,"abstract":"Visual question answering (VQA) lies at the intersection of language and vision research. It functions as a building block for multimodal conversational AI and serves as a testbed for assessing a model’s capability for open-domain scene understanding. While progress in this area was initially accelerated with the 2015 release of the popular and large dataset \"VQA\", new datasets are required to continue this research momentum. For example, the 2019 Outside Knowledge VQA dataset \"OKVQA\" extends VQA by adding more challenging questions that require complex, factual, and commonsense knowledge. However, in our analysis, we found that 41.4% of the dataset needed to be corrected and 10.6% needed to be removed. This paper describes the analysis, corrections, and removals completed and presents a new dataset: OK-VQA Version 2.0. To gain insights into the impact of the changes on OK-VQA research, the paper presents results on state-of-the-art models retrained with this new dataset. The side-by-side comparisons show that one method in particular, Knowledge Augmented Transformer for Vision-and-Language, extends its relative lead over competing methods. The dataset is available online.1","PeriodicalId":113072,"journal":{"name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128506844","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

NSV-TTS: Non-Speech Vocalization Modeling And Transfer In Emotional Text-To-Speech 情绪性文本到语音的非言语发声建模与迁移

ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2023-06-04 DOI: 10.1109/ICASSP49357.2023.10096033

Haitong Zhang, Xinyuan Yu, Yue Lin

引用次数: 1

A New Probabilistic Distance Metric with Application in Gaussian Mixture Reduction 一种新的概率距离度量及其在高斯混合约简中的应用

ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2023-06-04 DOI: 10.1109/ICASSP49357.2023.10096094

A. Sajedi, Y. Lawryshyn, K. Plataniotis

引用次数: 0

Managing Information Updating with Edge Computing: A Distributed and Learning Approach 基于边缘计算的信息更新管理:一种分布式学习方法

ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2023-06-04 DOI: 10.1109/ICASSP49357.2023.10095129

Junyi He, Di Zhang, Shumeng Liu, Yuezhi Zhou, Yaoxue Zhang

{"title":"Managing Information Updating with Edge Computing: A Distributed and Learning Approach","authors":"Junyi He, Di Zhang, Shumeng Liu, Yuezhi Zhou, Yaoxue Zhang","doi":"10.1109/ICASSP49357.2023.10095129","DOIUrl":"https://doi.org/10.1109/ICASSP49357.2023.10095129","url":null,"abstract":"The rapid proliferation of some real-time applications (e.g., video surveillance) has driven enormous interest in maximizing information freshness, quantified by the age of information (AoI). For some computation-intensive updates such as images or videos, the real-time update processing requires intensive resources, which edge servers can provide in mobile edge computing (MEC). In this paper, we investigate information updating scheduling with multiple users in MEC. Due to the centralized algorithms’ limitations in distributed systems where users are self-interested, we investigate an efficient distributed scheduling algorithm. We model the information updating scheduling as an uncooperative game and propose a distributed algorithm to compute the unique Nash equilibrium. Considering the unavailability of some global network information, we propose a learning algorithm where each user learns how to make decisions based on observable information in a distributed manner. Extensive evaluation results show the efficiency of the proposed algorithms.","PeriodicalId":113072,"journal":{"name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","volume":"253 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129046311","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Convergence of Stochastic PDMM 随机PDMM的收敛性

ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2023-06-04 DOI: 10.1109/ICASSP49357.2023.10095808

Sebastian O. Jordan, Thomas W. Sherson, R. Heusdens

引用次数: 1

Estimating Normalized Graph Laplacians in Financial Markets 金融市场中的归一化图拉普拉斯估计

ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2023-06-04 DOI: 10.1109/ICASSP49357.2023.10095870

José V. de M. Cardoso, Jiaxi Ying, Sandeep Kumar, D. Palomar

引用次数: 0

Group-Wise Co-Salient Object Detection with Siamese Transformers Via Brownian Distance Covariance Matching 基于布朗距离协方差匹配的暹罗变压器群智共显著目标检测

ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2023-06-04 DOI: 10.1109/ICASSP49357.2023.10096177

Yangjun Wu, H. Zhang, Lingyan Liang, Yaqian Zhao, Kaihua Zhang

{"title":"Group-Wise Co-Salient Object Detection with Siamese Transformers Via Brownian Distance Covariance Matching","authors":"Yangjun Wu, H. Zhang, Lingyan Liang, Yaqian Zhao, Kaihua Zhang","doi":"10.1109/ICASSP49357.2023.10096177","DOIUrl":"https://doi.org/10.1109/ICASSP49357.2023.10096177","url":null,"abstract":"Co-salient object detection (CoSOD) aims to discover and segment foreground targets in a group of images with the same semantic category. Existing mainstream approaches often employ convolutional neural networks (CNNs) to learn the semantic-invariant features from a group of images. Despite demonstrated success, there exist two limitations: 1) The CNNs introduce the inductive bias of locality that are difficult to model long-range dependency, limiting their feature representation capability. 2) Their models lack discriminability to differentiate semantic differences between different groups since only one group of images with the same semantic category has been taken into account for model training. To address these issues, this paper presents a Siamese Transformer architecture for CoSOD that can fully mine the group-wise semantic contrast information for more discriminative feature learning. Specifically, the designed Siamese Transformer takes two groups of images as input for feature contrastive learning. Each group is processed by a Transformer branch with shared weights to capture the long-range interaction information. Besides, to model the complex non-linear interactions between these two branches, we further design a Brownian distance covariance (BDC) module that uses joint distribution to measure the inter- and intra-group semantic similarity. The BDC can be efficiently calculated in closed form that can fully characterize independence for effective feature contrastive learning. Extensive evaluations on the three largest and most challenging benchmark datasets (CoSal2015, CoCA, and CoSOD3k) demonstrate the superiority of our method over a variety of state-of-the-art methods.","PeriodicalId":113072,"journal":{"name":"ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124627077","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Channel Estimation in Massive MIMO with Heavy-Tailed Noise: Gaussian-Mixture Versus Cauchy Models 含重尾噪声的大规模MIMO信道估计:高斯混合与柯西模型

ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) Pub Date : 2023-06-04 DOI: 10.1109/ICASSP49357.2023.10095925

Ziya Gülgün, E. Larsson

引用次数: 0