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arXiv 2018年

作者： Ge, Yinghao Zhang, Weile Gao, Feifei Zhang, Shun Ma, Xiaoli MOE Key Lab for Intelligent Networks and Network Security School of Electronic and Information Engineering Xi'an Jiaotong University Xi'an Shaanxi710049 China State Key Laboratory of Intelligent Technology and Systems Tsinghua National Laboratory for Information Science and Technology Department of Automation Tsinghua University Beijing100084 China State Key Laboratory of Integrated Services Networks Xidian University Xi'an Shaanxi710071 China Georgia Institute of Technology AtlantaGA30332 United States

Communications in high-mobility environments have caught a lot of attentions recently. In this paper, fast time-varying channels for massive multiple-input multiple-output (MIMO) systems are addressed. We derive the exact channel power spectrum density (PSD) for the uplink from a high-speed railway (HSR) to a base station (BS) and propose to further reduce the channel time variation via beamforming network optimization. A large-scale uniform linear array (ULA) is equipped at the HSR to separate multiple Doppler shifts in angle domain through high-resolution transmit beamforming. Each branch comprises a dominant Doppler shift, which can be compensated to suppress the channel time variation, and we derive the channel PSD and the Doppler spread to assess the residual channel time variation. Interestingly, the channel PSD can be exactly expressed as the product of a pattern function and a beam-distortion function. The former reflects the impact of array aperture and is the converted radiation pattern of ULA, while the latter depends on the configuration of beamforming directions. Inspired by the PSD analysis, we introduce a common configurable amplitudes and phases (CCAP) parameter to optimize the beamforming network, by partly removing the constant modulus quantized phase constraints of matched filter (MF) beamformers. In this way, the residual Doppler shifts can be ulteriorly suppressed, further reducing the residual channel time variation. The optimal CCAP parameter minimizing the Doppler spread is derived in a closed form. Numerical results are provided to corroborate both the channel PSD analysis and the superiority of beamforming network optimization technique. Copyright © 2018, The Authors. All rights reserved.

关键词： Beamforming

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Efficient Anonymous Attribute-Based Encryption with Access Policy Hidden for Cloud Computing 5

Efficient Anonymous Attribute-Based Encryption with Access P...

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2017 International Conference on Progress in Informatics and Computing(PIC)

作者： Chanying Huang Kedong Yan Songjie Wei Gongxuan Zhang Dong Hoon Lee School of Computer Science and Engineering Nanjing University of Science and Technology Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education Nanjing University of Science&Technology Graduate School of Information Security Korea University

ISBN: (纸本)9781538619797;9781538619780

Cloud computing is a revolutionary information technology paradigm, which provides users with unlimited, scalale, low-cost and convenient resource services, but when data is outsourced to a semi-trusted cloud server, challenging security issues such as user privacy, access control, etc. still urgently need to be addressed. Attribute-based encryption（ABE） scheme can provide sufficient data security and fine-grained access control for cloud data. However, the limitation of ABE is that user’s privacy would be disclosed with the access policy（structure） stored in clear text. Some works sacrificed the computing efficiency, key length or ciphertext size for privacy concerns. To overcome these problems, this paper proposes an efficient anonymous attributebased encryption scheme with access policy hidden. Using the idea of Boolean equivalent transformation, the proposed scheme can achieve fast encryption and protect the privacy for both data owner and legitimate access user. In addition, the proposed scheme can satisfy constant secret key length and reasonable size of ciphertext requirements. We conduct theoretical security analysis, and carry out experiments to prove that the proposed scheme has good performance in terms of computational, communication and storage overheads.

关键词： CP-ABE access policy hidden anonymity privacy efficiency

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A Privacy-Preserving Data Sharing Solution for Mobile Healthcare 5

A Privacy-Preserving Data Sharing Solution for Mobile Health...

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2017 International Conference on Progress in Informatics and Computing(PIC)

作者： Chanying Huang Kedong Yan Songjie Wei Dong Hoon Lee School of Computer Science and Engineering Nanjing University of Science and Technology Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education Nanjing University of Science&Technology Graduate School of Information Security Korea University

ISBN: (纸本)9781538619797;9781538619780

Personal Health Records（PHR） is patient-centric healthcare system, which allows patients to control who can get access to their health records and which section of the record can be accessed. Hot issues such as access control, patients control degree, and privacy protection, etc. are still the challenging concerns while designing a secure PHR *** this paper, we propose ds PPS, a secure integrated PHR framework（from health data collection to health data sharing）that meets patients’ full control of their PHR and sufficient privacy preservation. Specifically, ds PPS provides two schemes:Biometric-Based secure health data Collection（BBC） scheme and Attribute-Based health record Accessing（ABA） scheme. While BBC scheme enables patients to collect their scattered health data from multiple typical health systems securely and efficiently,the ABA scheme allows users（health systems） access to the PHR server with their sensitive attributes being protected. Comprehensive analysis is conducted to show the security of ds PPS against typical attacks. In addition, experiments in both smart phone and PC（Intel） platforms demonstrate that ds PPS produces reasonable performance in terms of storage, communication and computational overheads.

关键词： privacy-preserving security biometric attribute mobile health

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Changing life expectancy in European countries 1990–2021: a subanalysis of causes and risk factors from the Global Burden of Disease Study 2021

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The Lancet Public Health 2025年第3期10卷 e172-e188页

作者： Steel, Nicholas Bauer-Staeb, Clarissa Maria Mercedes Ford, John A. Abbafati, Cristiana Abdalla, Mohammed Altigani Abdelkader, Atef Abdi, Parsa Zuñiga, Roberto Ariel Abeldaño Abiodun, Olugbenga Olusola Abolhassani, Hassan Abu-Gharbieh, Eman Abukhadijah, Hana J. Abu-Zaid, Ahmed Addo, Isaac Yeboah Addolorato, Giovanni Adekanmbi, Victor Adetunji, Juliana Bunmi Adeyeoluwa, Temitayo Esther Agardh, Emilie E. Agyemang-Duah, Williams Ahmad, Danish Ahmed, Ayman Ahmed, Syed Anees Akinosoglou, Karolina Akkaif, Mohammed Ahmed Al Awaidy, Salah Al Hasan, Syed Mahfuz Al Zaabi, Omar Ali Mohammed Aldridge, Robert W. Algammal, Abdelazeem M. Al-Gheethi, Adel Ali Saeed Ali, Abid Ali, Mohammed Usman Ali, Syed Shujait Ali, Waad Alicandro, Gianfranco Alif, Sheikh Mohammad Al-Jumaily, Adel Allebeck, Peter Alrawashdeh, Ahmad Al-Rifai, Rami H Alsabri, Mohammed A. Alshahrani, Najim Z. Aluh, Deborah Oyine Al-Wardat, Mohammad Al-Zyoud, Walid A Amiri, Sohrab Anderlini, Deanna Andrei, Catalina Liliana Anil, Abhishek Anvari, Saeid Anyasodor, Anayochukwu Edward Appiah, Seth Christopher Yaw Aquilano, Michele Arabloo, Jalal Arafat, Mosab Areda, Demelash Aremu, Abdulfatai Armani, Keivan Armocida, Benedetta Ärnlöv, Johan Asaduzzaman, Muhammad Astell-Burt, Thomas Aujayeb, Avinash Ausloos, Marcel Azadnajafabad, Sina Aziz, Shahkaar Azzam, Ahmed Y. Babu, Giridhara Rathnaiah Badache, Andreea Corina Badiye, Ashish D. Bahramian, Saeed Baig, Atif Amin Baker, Jennifer L. Bansal, Hansi Bärnighausen, Till Winfried Barone, Mark Thomaz Ugliara Barrow, Amadou Barteit, Sandra Bashir, Shahid Bashiru, Hameed Akande Basso, João Diogo Bastan, Mohammad-Mahdi Basu, Sanjay Batra, Kavita Bauckneht, Matteo Baune, Bernhard T. Beghi, Massimiliano Beiranvand, Maryam Béjot, Yannick Bell, Michelle L. Bello, Olorunjuwon Omolaja Belo, Luis Beloukas, Apostolos Beneke, Alice A. Bettencourt, Paulo J G Bhagavathula, Akshaya Srikanth Bhala, Neeraj Bhaskar, Sonu Bisulli, Francesca Bjørge, Tone Bodunrin, Aadam Olalekan Carvajal, Alejandro Botero Bouaoud, Souad Brayne, Carol Brenner, Herm Department of Primary Care and Public Health University of East Anglia Norwich United Kingdom Office for Health Improvement and Disparity Department of Health and Social Care London United Kingdom Office for Health Improvement and Disparities Department of Health and Social Care London United Kingdom Department of Legal and Economic Studies La Sapienza University Rome Italy Rome Italy Hull York Medical School University of Hull Hull United Kingdom Department of Mathematics and Sciences Ajman University Ajman United Arab Emirates Department of Medicine Memorial University St. John's NL Canada Postgraduate Department University of Sierrasur Miahuatlan de Porfirio Diaz Mexico Yhteiskuntadatatieteen Keskus University of Helsinki Helsinki Finland Department of Internal Medicine Federal Medical Centre Abuja Nigeria Research Center for Immunodeficiencies Tehran University of Medical Sciences Tehran Iran Department of Medical Biochemistry and Biophysics Stockholm Sweden Department of Clinical Sciences University of Sharjah Sharjah United Arab Emirates Department of Biopharmaceutics and Clinical Pharmacy University of Jordan Amman Jordan Medical Research Center Hamad Medical Corporation Doha Qatar Department of Biochemistry and Molecular Medicine Alfaisal University Riyadh Saudi Arabia College of Graduate Health Sciences University of Tennessee Memphis TN United States School of Medicine University of Sydney Sydney NSW Australia Centre for Social Research in Health University of New South Wales Sydney NSW Australia Internal Medicine and Alcohol Related Disease Unit Fondazione Policlinico Universitario A. Gemelli IRCCS Rome Italy Department of Medical and Surgical Sciences Università Cattolica di Roma (Catholic University of Rome) Rome Italy Department of Obstetrics and Gynecology University of Texas Medical Branch Galveston TX United States Department of Biochemistry Osun State University Osogbo Nigeria Department of Pharmacology and Therapeutics U

Background: Decades of steady improvements in life expectancy in Europe slowed down from around 2011, well before the COVID-19 pandemic, for reasons which remain disputed. We aimed to assess how changes in risk factors and cause-specific death rates in different European countries related to changes in life expectancy in those countries before and during the COVID-19 pandemic. Methods: We used data and methods from the Global Burden of Diseases, Injuries, and Risk Factors Study 2021 to compare changes in life expectancy at birth, causes of death, and population exposure to risk factors in 16 European Economic Area countries (Austria, Belgium, Denmark, Finland, France, Germany, Greece, Iceland, Ireland, Italy, Luxembourg, the Netherlands, Norway, Portugal, Spain, and Sweden) and the four UK nations (England, Northern Ireland, Scotland, and Wales) for three time periods: 1990–2011, 2011–19, and 2019–21. Changes in life expectancy and causes of death were estimated with an established life expectancy cause-specific decomposition method, and compared with summary exposure values of risk factors for the major causes of death influencing life expectancy. Findings: All countries showed mean annual improvements in life expectancy in both 1990–2011 (overall mean 0·23 years [95% uncertainty interval [UI] 0·23 to 0·24]) and 2011–19 (overall mean 0·15 years [0·13 to 0·16]). The rate of improvement was lower in 2011–19 than in 1990–2011 in all countries except for Norway, where the mean annual increase in life expectancy rose from 0·21 years (95% UI 0·20 to 0·22) in 1990–2011 to 0·23 years (0·21 to 0·26) in 2011–19 (difference of 0·03 years). In other countries, the difference in mean annual improvement between these periods ranged from –0·01 years in Iceland (0·19 years [95% UI 0·16 to 0·21] vs 0·18 years [0·09 to 0·26]), to –0·18 years in England (0·25 years [0·24 to 0·25] vs 0·07 years [0·06 to 0·08]). In 2019–21, there was an overall decrease in mean annual life expectancy a

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HPC AI500: A benchmark suite for HPC AI systems

arXiv

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arXiv 2019年

作者： Jiang, Zihan Gao, Wanling Wang, Lei Xiong, Xingwang Zhang, Yuchen Wen, Xu Luo, Chunjie Ye, Hainan Lu, Xiaoyi Zhang, Yunquan Feng, Shengzhong Li, Kenli Xu, Weijia Zhan, Jianfeng State Key Laboratory of Computer Architecture Institute of Computing Technology Chinese Academy of Sciences University of Chinese Academy of Sciences China BenchCouncil [International Open Benchmarking Council Beijing Academy of Frontier Sciences and Technology State University of New York Buffalo United States Department of Computer Science and Engineering Ohio State University National Supercomputing Center Shenzhen China National Supercomputing Center Changsha China National Supercomputing Center Jinan China Texas Advanced Computing Center Texas University Austin United States

In recent years, with the trend of applying deep learning (DL) in high performance scientific computing, the unique characteristics of emerging DL workloads in HPC raise great challenges in designing, implementing HPC AI systems. The community needs a new yard stick for evaluating the future HPC systems. In this paper, we propose HPC AI500 - a benchmark suite for evaluating HPC systems that running scientific DL workloads. Covering the most representative scientific fields, each workload from HPC AI500 is based on real-world scientific DL applications. Currently, we choose 14 scientific DL benchmarks from perspectives of application scenarios, data sets, and software stack. We propose a set of metrics for comprehensively evaluating the HPC AI systems, considering both accuracy, performance as well as power and cost. We provide a scalable reference implementation of HPC AI500. The specification and source code are publicly available from http://***/HPCAI500/***. Meanwhile, the AI benchmark suites for datacenter, IoT, Edge are also released on the BenchCouncil web site. Copyright © 2019, The Authors. All rights reserved.

关键词： Benchmarking

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Pursuit of paired dijet resonances in the Run 2 dataset with ATLAS

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Physical Review D 2023年第11期108卷 112005-112005页

作者： G. Aad B. Abbott K. Abeling N. J. Abicht S. H. Abidi A. Aboulhorma H. Abramowicz H. Abreu Y. Abulaiti B. S. Acharya C. Adam Bourdarios L. Adamczyk S. V. Addepalli M. J. Addison J. Adelman A. Adiguzel T. Adye A. A. Affolder Y. Afik M. N. Agaras J. Agarwala A. Aggarwal C. Agheorghiesei A. Ahmad F. Ahmadov W. S. Ahmed S. Ahuja X. Ai G. Aielli A. Aikot M. Ait Tamlihat B. Aitbenchikh I. Aizenberg M. Akbiyik T. P. A. Åkesson A. V. Akimov D. Akiyama N. N. Akolkar K. Al Khoury G. L. Alberghi J. Albert P. Albicocco G. L. Albouy S. Alderweireldt M. Aleksa I. N. Aleksandrov C. Alexa T. Alexopoulos F. Alfonsi M. Algren M. Alhroob B. Ali H. M. J. Ali S. Ali S. W. Alibocus M. Aliev G. Alimonti W. Alkakhi C. Allaire B. M. M. Allbrooke J. F. Allen C. A. Allendes Flores P. P. Allport A. Aloisio F. Alonso C. Alpigiani M. Alvarez Estevez A. Alvarez Fernandez M. Alves Cardoso M. G. Alviggi M. Aly Y. Amaral Coutinho A. Ambler C. Amelung M. Amerl C. G. Ames D. Amidei S. P. Amor Dos Santos K. R. Amos V. Ananiev C. Anastopoulos T. Andeen J. K. Anders S. Y. Andrean A. Andreazza S. Angelidakis A. Angerami A. V. Anisenkov A. Annovi C. Antel M. T. Anthony E. Antipov M. Antonelli F. Anulli M. Aoki T. Aoki J. A. Aparisi Pozo M. A. Aparo L. Aperio Bella C. Appelt A. Apyan N. Aranzabal S. J. Arbiol Val C. Arcangeletti A. T. H. Arce E. Arena J-F. Arguin S. Argyropoulos J.-H. Arling O. Arnaez H. Arnold G. Artoni H. Asada K. Asai S. Asai N. A. Asbah J. Assahsah K. Assamagan R. Astalos S. Atashi R. J. Atkin M. Atkinson H. Atmani P. A. Atmasiddha K. Augsten S. Auricchio A. D. Auriol V. A. Austrup G. Avolio K. Axiotis G. Azuelos D. Babal H. Bachacou K. Bachas A. Bachiu F. Backman A. Badea P. Bagnaia M. Bahmani A. J. Bailey V. R. Bailey J. T. Baines L. Baines O. K. Baker E. Bakos D. Bakshi Gupta V. Balakrishnan R. Balasubramanian E. M. Baldin P. Balek E. Ballabene F. Balli L. M. Baltes W. K. Balunas J. Balz E. Banas M. Bandieramonte A. Bandyopadhyay S. Bansal L. Barak M. Barakat E. L. Barberio D. Barberis M. Barbero M. Z. Barel K. N. Barends T. Barill CPPM Aix-Marseille Université CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman Oklahoma USA II. Physikalisches Institut Georg-August-Universität Göttingen Göttingen Germany Fakultät Physik Technische Universität Dortmund Dortmund Germany Physics Department Brookhaven National Laboratory Upton New York USA Faculté des sciences Université Mohammed V Rabat Morocco Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel Department of Physics Technion Israel Institute of Technology Haifa Israel Department of Physics New York University New York New York USA INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy LAPP Université Savoie Mont Blanc CNRS/IN2P3 Annecy France AGH University of Krakow Faculty of Physics and Applied Computer Science Krakow Poland Department of Physics Brandeis University Waltham Massachusetts USA School of Physics and Astronomy University of Manchester Manchester United Kingdom Department of Physics Northern Illinois University DeKalb Illinois USA Department of Physics Istanbul University Istanbul Türkiye Particle Physics Department Rutherford Appleton Laboratory Didcot United Kingdom Santa Cruz Institute for Particle Physics University of California Santa Cruz Santa Cruz California USA CERN Geneva Switzerland Institut de Física d’Altes Energies (IFAE) Barcelona Institute of Science and Technology Barcelona Spain INFN Sezione di Pavia Pavia Italy Dipartimento di Fisica Università di Pavia Pavia Italy Institut für Physik Universität Mainz Mainz Germany Department of Physics Alexandru Ioan Cuza University of Iasi Iasi Romania Affiliated with an international laboratory covered by a cooperation agreement with CERN Department of Physics McGill University Montreal Quebec Canada Department of Physics Royal Holloway University of London Egham United Kingdom Department of Modern Physics and

New particles with large masses that decay into hadronically interacting particles are predicted by many models of physics beyond the Standard Model. A search for a massive resonance that decays into pairs of dijet resonances is performed using 140 fb−1 of proton-proton collisions at s=13 TeV recorded by the ATLAS detector during Run 2 of the Large Hadron Collider. Resonances are searched for in the invariant mass of the tetrajet system, and in the average invariant mass of the pair of dijet systems. A data-driven background estimate is obtained by fitting the tetrajet and dijet invariant mass distributions with a four-parameter dijet function and a search for local excesses from resonant production of dijet pairs is performed. No significant excess of events beyond the Standard Model expectation is observed, and upper limits are set on the production cross sections of new physics scenarios.

关键词： Signatures with jets Hypothetical particles Particle data analysis

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Deep discriminant analysis for I-vector based robust speaker recognition

arXiv

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arXiv 2018年

作者： Wang, Shuai Huang, Zili Qian, Yanmin Yu, Kai Key Laboratory of Shanghai Education Commission for Intelligent Interaction Cognitive Engineering SpeechLab Department of Computer Science and Engineering Brain Science and Technology Research Center Shanghai Jiao Tong University Shanghai China

Linear Discriminant Analysis (LDA) has been used as a standard post-processing procedure in many state-of-the-art speaker recognition tasks. Through maximizing the inter-speaker difference and minimizing the intra-speaker variation, LDA projects i-vectors to a lower-dimensional and more discriminative subspace. In this paper, we propose a neural network based compensation scheme(termed as deep discriminant analysis, DDA) for i-vector based speaker recognition, which shares the spirit with LDA. Optimized against softmax loss and center loss at the same time, the proposed method learns a more compact and discriminative embedding space. Compared with the Gaussian distribution assumption of data and the learnt linear projection in LDA, the proposed method doesn't pose any assumptions on data and can learn a non-linear projection function. Experiments are carried out on a short-duration text-independent dataset based on the SRE Corpus, noticeable performance improvement can be observed against the normal LDA or PLDA methods. Copyright © 2018, The Authors. All rights reserved.

关键词： Discriminant analysis

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Joint I-Vector with End-to-End System for Short Duration Text-Independent Speaker Verification

Joint I-Vector with End-to-End System for Short Duration Tex...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Zili Huang Shuai Wang Yanmin Qian Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering SpeechLab Department of Computer Science and Engineering Brain Science and Technology Research Center Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781538646595

Factor analysis based i-vector has been the state-of-the-art method for speaker verification. Recently, researchers propose to build DNN based end-to-end speaker verification systems and achieve comparable performance with i -vector. Since these two methods possess their own property and differ from each other significantly, we explore a framework to integrate these two paradigms together to utilize their complementarity. More specifically, in this paper we develop and compare four methodologies to integrate traditional i -vector into end-to-end systems, including score fusion, embeddings concatenation, transformed concatenation and joint learning. All these approaches achieve significant gains. Moreover, the hard trial selection is performed on the end-to-end architecture which further improves the performance. Experimental results on a text-independent short-duration dataset generated from SRE 2010 reveal that the newly proposed method reduces the EER by relative 31.0% and 28.2% compared to the i-vector and end-to-end baselines respectively.

关键词： speaker verification end-to-end i-vector triplet loss hard trial selection speaker recognition end-to-end end system Loudspeakers Joints energy efficiency ratio Short circuits

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FOCAL KL-DIVERGENCE BASED DILATED CONVOLUTIONAL NEURAL NETWORKS FOR CO-CHANNEL SPEAKER IDENTIFICATION

FOCAL KL-DIVERGENCE BASED DILATED CONVOLUTIONAL NEURAL NETWO...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Shuai Wang Yanmin Qian Kai Yu Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering SpeechLab Department of Computer Science and Engineering Brain Science and Technology Research Center Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781538646595

Recognizing the identities of multiple talkers via their overlapped speech is a challenging task, it is also one main difficulty for the "cocktail party problem". In this paper, a novel dilated convolutional neural network with a focal KL-divergence loss function is proposed to tackle this problem. During training, relative loss for the well-classified samples is automatically reduced and consequently more attention is paid to the hard samples. The use of the focal KL-divergence loss function leads to more stable training and improved testing performance. Furthermore, a post processing of assigning different frames with different weights is also adopted and leads to further improvement. The proposed framework can be easily extended from 2-talker to 3-talker speaker identification scenario. Experiments on the artificially generated RSR2015 multi-talker mixed corpus show that the proposed approach can improve multi-talker speaker identification significantly.

关键词： co-channel speaker identification convolutional neural networks focal loss dilated convolution Loudspeakers Neural network speaker recognition personal identity

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Robust Spoken Language Understanding with Unsupervised ASR-Error Adaptation

Robust Spoken Language Understanding with Unsupervised ASR-E...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Su Zhu Ouyu Lan Kai Yu Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering SpeechLab Department of Computer Science and Engineering Brain Science and Technology Research Center Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781538646595

Robustness to errors produced by automatic speech recognition (ASR) is essential for Spoken Language Understanding (SLU). Traditional robust SLU typically needs ASR hypotheses with semantic annotations for training. However, semantic annotation is very expensive, and the corresponding ASR system may change frequently. Here, we propose a novel unsupervised ASR-error adaptation method, obviating the need of annotated ASR hypotheses. It only requires semantically annotated transcripts for the slot-tagging task and the transcripts paired with hypotheses for an input sentence reconstruction task. In this method, feature encoders which share part of the parameters are exploited to enforce the tasks in a similar feature space. Therefore, the transcript side slot-tagging model can be transferred to ASR hypotheses side easily. Experiments show that the proposed approach can yield significant improvement over strong baselines, and achieve performance very close to the oracle system.

关键词： Spoken Language understanding ASR-error robustness adversarial adaptation spoken language understanding Speech recognition aquifer storage and recovery spoken language Eigenvector transcript Religious Missions ANNOTATIONS

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