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相关论文: SUT System Description for NIST SRE 2016

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This paper presents a description of STC Ltd. systems submitted to the NIST 2021 Speaker Recognition Evaluation for both fixed and open training conditions. These systems consists of a number of diverse subsystems based on using deep neural…

This document briefly describes the systems submitted by the Center for Robust Speech Systems (CRSS) from The University of Texas at Dallas (UTD) to the 2016 National Institute of Standards and Technology (NIST) Speaker Recognition…

计算与语言 · 计算机科学 2016-10-26 Chunlei Zhang , Fahimeh Bahmaninezhad , Shivesh Ranjan , Chengzhu Yu , Navid Shokouhi , John H. L. Hansen

The CL-UZH team submitted one system each for the fixed and open conditions of the NIST SRE 2024 challenge. For the closed-set condition, results for the audio-only trials were achieved using the X-vector system developed with Kaldi. For…

音频与语音处理 · 电气工程与系统科学 2025-10-08 Aref Farhadipour , Shiran Liu , Masoumeh Chapariniya , Valeriia Vyshnevetska , Srikanth Madikeri , Teodora Vukovic , Volker Dellwo

The NIST Speaker Recognition Evaluation - Conversational Telephone Speech (CTS) challenge 2019 was an open evaluation for the task of speaker verification in challenging conditions. In this paper, we provide a detailed account of the LEAP…

音频与语音处理 · 电气工程与系统科学 2020-05-26 Shreyas Ramoji , Prashant Krishnan , Bhargavram Mysore , Prachi Singh , Sriram Ganapathy

This manuscript describes the I4U submission to the 2020 NIST Speaker Recognition Evaluation (SRE'20) Conversational Telephone Speech (CTS) Challenge. The I4U's submission was resulted from active collaboration among researchers across…

This work describes the speaker verification system developed by Human Language Technology Laboratory, National University of Singapore (HLT-NUS) for 2019 NIST Multimedia Speaker Recognition Evaluation (SRE). The multimedia research has…

音频与语音处理 · 电气工程与系统科学 2020-10-09 Rohan Kumar Das , Ruijie Tao , Jichen Yang , Wei Rao , Cheng Yu , Haizhou Li

This paper presents the system description of the THUEE team for the NIST 2020 Speaker Recognition Evaluation (SRE) conversational telephone speech (CTS) challenge. The subsystems including ResNet74, ResNet152, and RepVGG-B2 are developed…

声音 · 计算机科学 2022-10-13 Yu Zheng , Jinghan Peng , Miao Zhao , Yufeng Ma , Min Liu , Xinyue Ma , Tianyu Liang , Tianlong Kong , Liang He , Minqiang Xu

This paper describes the LIA speaker recognition system developed for the Speaker Recognition Evaluation (SRE) campaign. Eight sub-systems are developed, all based on a state-of-the-art approach: i-vector/PLDA which represents the…

This paper presents the Intelligent Voice (IV) system submitted to the NIST 2016 Speaker Recognition Evaluation (SRE). The primary emphasis of SRE this year was on developing speaker recognition technology which is robust for novel…

声音 · 计算机科学 2016-11-03 Abbas Khosravani , Cornelius Glackin , Nazim Dugan , Gérard Chollet , Nigel Cannings

Vision Transformers (ViT)s have shown great performance in self-supervised learning of global and local representations that can be transferred to downstream applications. Inspired by these results, we introduce a novel self-supervised…

计算机视觉与模式识别 · 计算机科学 2022-03-29 Yucheng Tang , Dong Yang , Wenqi Li , Holger Roth , Bennett Landman , Daguang Xu , Vishwesh Nath , Ali Hatamizadeh

This paper describes the systems submitted by the department of electronic engineering, institute of microelectronics of Tsinghua university and TsingMicro Co. Ltd. (THUEE) to the NIST 2019 speaker recognition evaluation CTS challenge. Six…

This work provides a brief description of Human Language Technology (HLT) Laboratory, National University of Singapore (NUS) system submission for 2020 NIST conversational telephone speech (CTS) speaker recognition evaluation (SRE). The…

音频与语音处理 · 电气工程与系统科学 2021-11-15 Rohan Kumar Das , Ruijie Tao , Haizhou Li

Large, self-supervised vision models have led to substantial advancements for automatically interpreting natural images. Recent works have begun tailoring these methods to remote sensing data which has rich structure with multi-sensor,…

计算机视觉与模式识别 · 计算机科学 2023-12-06 Jeremy Irvin , Lucas Tao , Joanne Zhou , Yuntao Ma , Langston Nashold , Benjamin Liu , Andrew Y. Ng

We propose a novel approach for the development, analysis, and verification of reductions between NP-complete problems. This method uses the URSA system, a SAT-based constraint solver and incorporates features that distinguish it from…

计算机科学中的逻辑 · 计算机科学 2025-11-25 Predrag Janičić

The 2021 Speaker Recognition Evaluation (SRE21) was the latest cycle of the ongoing evaluation series conducted by the U.S. National Institute of Standards and Technology (NIST) since 1996. It was the second large-scale multimodal…

音频与语音处理 · 电气工程与系统科学 2022-04-22 Seyed Omid Sadjadi , Craig Greenberg , Elliot Singer , Lisa Mason , Douglas Reynolds

This paper describes our system on SemEval-2023 Task 10: Explainable Detection of Online Sexism (EDOS). This work aims to design an automatic system for detecting and classifying sexist content in online spaces. We propose a set of…

计算与语言 · 计算机科学 2023-05-12 Hadiseh Mahmoudi

Parameters of the mathematical model describing many practical dynamical systems are prone to vary due to aging or renewal, wear and tear, as well as changes in environmental or service conditions. These variabilities will adversely affect…

系统与控制 · 电气工程与系统科学 2022-07-13 Hang Geng , Mulugeta A. Haile , Huazhen Fang

This paper gives an overview of previous work in which the authors used NASA's Formal Requirement Elicitation Tool (FRET) to formalise requirements. We discuss four case studies where we used FRET to capture the system's requirements. These…

软件工程 · 计算机科学 2025-04-01 Marie Farrell , Matt Luckcuck , Rosemary Monahan , Conor Reynolds , Oisín Sheridan

This paper introduces an approach to enhance seismic fault recognition through self-supervised pretraining. Seismic fault interpretation holds great significance in the fields of geophysics and geology. However, conventional methods for…

计算机视觉与模式识别 · 计算机科学 2024-01-10 Zeren Zhang , Ran Chen , Jinwen Ma
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