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Differential Impacts of Monologue and Conversation on Speech Emotion Recognition

IEEE Transactions on Affective Computing 2024年第2期16卷 485-498页

作者： Chien, Woan-Shiuan Upadhyay, Shreya G. Lin, Wei-Cheng Busso, Carlos Lee, Chi-Chun National Tsing Hua University Department of Electrical Engineering Taiwan The University of Texas at Dallas Erik Jonsson School of Engineering & Commputer Science RichardsonTX United States Carnegie Mellon University Language Technologies Institute School of Computer Science PittsburghPA15213 United States

The advancement of Speech Emotion Recognition (SER) is significantly dependent on the quality of emotional speech corpora used for model training. Researchers in the field of SER have developed various corpora by adjusting design parameters to enhance the reliability of the training source. For this study, we focus on exploring communication modes of collection, specifically analyzing spontaneous emotional speech patterns gathered during conversation or monologue. While conversations are acknowledged as effective for eliciting authentic emotional expressions, systematic analyses are necessary to confirm their reliability as a better source of emotional speech data. We investigate this research question from perceptual differences and acoustic variability present in both emotional speeches. Our analyses on multi-lingual corpora show that, first, raters exhibit higher consistency for conversation recordings when evaluating categorical emotions, and second, perceptions and acoustic patterns observed in conversational samples align more closely with expected trends discussed in relevant emotion literature. We further examine the impact of these differences on SER modeling, which shows that we can train a more robust and stable SER model by using conversation data. This work provides comprehensive evidence suggesting that conversation may offer a better source compared to monologue for developing an SER model. © 2010-2012 IEEE.

关键词： Speech analysis

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Measurement of emissivity with a new grey body and novel IR thermal sensor dubbed TMOS

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红外与毫米波学报 2025年第1期44卷 17-24页

作者： Moshe Avraham Shlomi Bouscher Jonathan Nemirovsky Yael Nemirovsky 无 Electrical and Computer Engineering Department Technion-Israel Institute of TechnologyHaifaIsrael TODOS-Technologies Airport CityIsrael

The concept of emissivity has been with the scientific and engineering world since Planck formulated his blackbody radiation law more than a century ***,emissivity is an elusive concept even for ex⁃*** is a vague and fuzzy concept for the wider community of *** importance of remote sensing of temperature by measuring IR radiation has been recognized in a wide range of industrial,medical,and environ⁃mental *** of the major sources of errors in IR radiometry is the emissivity of the surface being *** real experiments,emissivity may be influenced by many factors:surface texture,spectral properties,oxida⁃tion,and aging of *** commercial blackbodies are prevalent,the much-needed grey bodies with a known emissivity,are *** study describes how to achieve a calibrated and stable emissivity with a blackbody,a perforated screen,and a reliable and linear novel IR thermal sensor,18 dubbed *** Digital TMOS is now a low-cost commercial product,it requires low power,and it has a small form *** method⁃ology is based on two-color measurements,with two different optical filters,with selected wavelengths conform⁃ing to the grey body definition of the use case under *** a photochemically etched perforated screen,the effective emissivity of the screen is simply the hole density area of the surface area that emits according to the blackbody temperature *** concept is illustrated with ray tracing simulations,which demonstrate the *** results are reported.

关键词： blackbody grey body graybody cavity blackbody extended area blackbody emissivity IR thermometry remote temperature measurement

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Effect of individual atmospheric parameters on beam spreading of higher-order Gaussian beam

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Optical and Quantum Electronics 2024年第12期56卷 1-18页

作者： kumar, Mukesh Khandelwal, Arpit Azeemuddin, Syed Center for VLSI and Embedded System Technologies International Institute of Information Technology Hyderabad India Department of Electrical Engineering Indian Institute of Technology Jodhpur India Department of Electrical and Computer Engineering Behrend College Penn State University EriePA United States

The beam spreading is essential for evaluating the higher-order Gaussian beam when it propagates through atmospheric turbulence. In this paper, we investigate the impact of individual atmospheric parameters such as jitter, turbulence, wind speed, and thermal blooming on beam spreading of Hermite Gaussian (HG), and Laguerre Gaussian (LG) beams. We also examine spot size variations due to beam quality on various HG and LG modes. It is seen that the impact of spreading caused by beam quality and turbulence is higher than that of jitter, wind speed, and thermal blooming. As the mode order increases, the effect of turbulence strength increases, leading to more spread for HG and LG beams. Spreading due to diffraction and beam quality on higher mode LG beam is higher than the HG beam in different modes. Beam spreading due to thermal blooming for the lower mode is higher compared to the higher mode for LG and HG beams. The sensitivity of higher mode LG beams to turbulence distortions is greater than HG beams as they experience more significant fractional increases in their spot size due to turbulence. The combined beam spread for the Laguerre Gaussian beam is larger than the Hermite Gaussian beam. This paper aims to understand better individual beam spreading in the atmosphere and its impact on the overall performance of higher-order laser propagation to develop optimized laser systems. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Gaussian beams

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Millimeter-Wave GaAs Ultra-Wideband Medium Power Amplifier and Broadband High-Power Power Amplifier for 5G/6G Applications

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IEEE Journal on Emerging and Selected Topics in Circuits and Systems 2024年第1期14卷 111-121页

作者： Fu, Zi-Hao Li, Ming-Xuan Ma, Tzyh-Ghuang Wu, Chan-Shin Lin, Kun-You National Taiwan University Graduate Institute of Communication Engineering Department of Electrical Engineering Taipei10617 Taiwan National Taiwan University of Science and Technology Department of Electrical Engineering Taipei10607 Taiwan ASUSTek Computer Inc. Taipei11259 Taiwan Ultraband Technologies Inc. Taipei11158 Taiwan

This paper presents an ultra-wideband (UWB) medium power amplifier (MPA) and a broadband high-power power amplifier (HPA) operating at the 5G/6G frequency bands. By using 0.15~\mu \text{m} GaAs pseudomorphic high electron mobility transistor (pHEMT) technology process, the proposed UWB MPA delivers an average small-signal gain of 16.5 dB, a saturation output power (\text{P}_{\mathrm {sat}} ) of 24 dBm, and a peak power-added efficiency (PAE) over 24% from 24 to 38 GHz with a chip area of 2\times1 mm2. The broadband HPA demonstrates a 17-dB average small-signal gain, 29-dBm \text{P}_{\mathrm {sat}} , and a PAE over 28% from 24 to 32 GHz with a 2.4\times1.1 mm2 chip size. The measurement results have demonstrated the great potential of the proposed PA for 5G/6G millimeter-wave applications. © 2011 IEEE.

关键词： Power amplifiers

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An Intelligent Traffic Management of Vehicles using Deep Learning Approach in Smart Cities 3

An Intelligent Traffic Management of Vehicles using Deep Lea...

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3rd International Conference on Integrated Circuits and Communication Systems, ICICACS 2025

作者： Elov, Botir Dauletov, Adilbek Sucharitha, Yadala Khalilova, Feruza Latipova, Mukhayyo Abdullayeva, Mukhtasarkhon Alisher Navo'i Tashkent State University of Uzbek Language and Literature Tashkent Uzbekistan Alfraganus University Department of Digital Technologies Tashkent Uzbekistan Vnr Vignana Jyothi Institute of Engineering and Technology Department of Computer Science and Engineering Hyderabad India Fergana Polytechnic Institute Department of Electrical Power Engineering Fergana Uzbekistan

ISBN: (纸本)9798331508456

Smart traffic management of automobiles has been one of the utmost sought-after issues in the academic community due to the ever-increasing pace of urbanization and civilization over the last several centuries. Vehicle dissection, traffic density appraisal, and vehicle tracing are the three main components of smart traffic management. This problem becomes more difficult to resolve when there are occlusions, background clutter, and fluctuations in traffic density. In light of this need, we explore a deeper learning approach based on R-CNN s for faster vehicle segmentation in this study. There is adaptive backdrop modeling in the computational framework. It solves problems with lighting and shadows as well. The use of topological active net deformable models allows for segmentation that is more precise. The deformations mentioned can be accomplished with the aid of topological and stretched topological active nets. Minimizing energy allows for mesh deformation. Using a tweaked version of the stretched topological active net improves the segmentation accuracy to 98.3%. The investigational findings show that this framework is better than other methods. © 2025 IEEE.

关键词： Highway administration

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Noise-Robust Speech Emotion Recognition Using Shared Self-Supervised Representations with Integrated Speech Enhancement

Noise-Robust Speech Emotion Recognition Using Shared Self-Su...

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

作者： Tzeng, Jing-Tong Leem, Seong-Gyun Salman, Ali N. Lee, Chi-Chun Busso, Carlos College of Semiconductor Research National Tsing Hua University Taiwan Department of Electrical and Computer Engineering The University of Texas Dallas United States Department of Electrical Engineering National Tsing Hua University Taiwan Language Technologies Institute Carnegie Mellon University United States

ISBN: (纸本)9798350368741

Recent studies have demonstrated the effectiveness of fine-tuning self-supervised speech representation models for speech emotion recognition (SER). However, applying SER in real-world environments remains challenging due to pervasive noise. Relying on low-accuracy predictions due to noisy speech can undermine the user's trust. This paper proposes a unified self-supervised speech representation framework for enhanced speech emotion recognition designed to increase noise robustness in SER while generating enhanced speech. Our framework integrates speech enhancement (SE) and SER tasks, leveraging shared self-supervised learning (SSL)-derived features to improve emotion classification performance in noisy environments. This strategy encourages the SE module to enhance discriminative information for SER tasks. Additionally, we introduce a cascade unfrozen training strategy, where the SSL model is gradually unfrozen and fine-tuned alongside the SE and SER heads, ensuring training stability and preserving the generalizability of SSL representations. This approach demonstrates improvements in SER performance under unseen noisy conditions without compromising SE quality. When tested at a 0 dB signal-to-noise ratio (SNR) level, our proposed method outperforms the original baseline by 3.7% in F1-Macro and 2.7% in F1-Micro scores, where the differences are statistically significant. © 2025 IEEE.

关键词： multitask learning noisy speech Speech emotion recognition speech enhancement

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Phonetically-Anchored Domain Adaptation for Cross-Lingual Speech Emotion Recognition

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IEEE Transactions on Affective Computing 2025年

作者： Upadhyay, Shreya G. Martinez-Lucas, Luz Katz, William Busso, Carlos Lee, Chi-Chun Department of Electrical Engineering National Tsing Hua University Taiwan Department of Electrical and Computer Engineering University of Texas at Dallas United States Department of Speech Language and Hearing Department of Electrical and Computer Engineering University of Texas at Dallas United States Language Technologies Institute School of Computer Science Carnegie Mellon University United States

The prevalence of cross-lingual speech emotion recognition (SER) modeling has significantly increased due to its wide range of applications. Previous studies have primarily focused on technical strategies to adapt features, domains, and labels across languages, often overlooking the underlying commonalities between the languages. In this study, we address the language adaptation challenge in cross-lingual scenarios by incorporating vowel-phonetic constraints. Our approach is structured in two main parts. Firstly, we investigate the vowel-phonetic commonalities associated with specific emotions across languages, particularly focusing on common vowels that prove to be valuable for SER modeling. Secondly, we utilize these identified common vowels as anchors to facilitate cross-lingual SER. To demonstrate the effectiveness of our approach, we conduct case studies using American English and Taiwanese Mandarin with two naturalistic emotional speech corpora: the MSP-Podcast and BIIC-Podcast corpora. The approach leverages evidence that certain vowels, including monophthongs and diphthongs, exhibit emotion-specific commonality across languages, serving as phonetic anchors to enhance unsupervised cross-lingual SER learning. The proposed model surpasses baseline performance, highlighting the importance of phonetic similarities for effective language adaptation in cross-lingual SER scenarios. © 2010-2012 IEEE.

关键词： Emotion Recognition

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Data management in Ethereum DApps: A cost and performance analysis

Data management in Ethereum DApps: A cost and performance an...

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作者： Kostamis, Periklis Sendros, Andreas Efraimidis, Pavlos S. Department of Electrical and Computer Engineering Democritus University of Thrace Xanthi67100 Greece Institute for Language and Speech Processing Athena Research Center Xanthi67100 Greece

The cost of interacting with a blockchain and the time required to search and retrieve information from it are important factors in the design of Decentralized Applications (DApps). The corresponding approaches for data management in Ethereum vary from pure on-chain solutions to hybrid architectures. In this work, we thoroughly examine a wide range of data management methods, including unconventional ones, and evaluate them in terms of storage cost and retrieval latency while considering the impact of recent hard forks. More precisely, we elaborate on the use of Smart Contract (SC) storage as a data store for DApps and in view of the prohibitive cost inherent to this approach, we present and compare methods for low-cost data handling in Ethereum, namely the event-logs, the transaction payload, and the almost surprising exploitation of unused function arguments. In addition, we study hybrid schemes by using IPFS and Swarm as storage platforms and Ethereum as a timestamping proof mechanism. Such schemes are especially effective when large chunks of data have to be managed. The upload and retrieval performance of these platforms and the cost associated with storing (on-chain) the identifiers of the uploaded data are of utmost importance and therefore are investigated in detail. © 2023

关键词： Smart contract

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Security and Privacy Challenges in SDN-Enabled IoT Systems: Causes, Proposed Solutions,and Future Directions

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computers, Materials & Continua 2024年第8期80卷 2511-2533页

作者： Ahmad Rahdari Ahmad Jalili Mehdi Esnaashari Mehdi Gheisari Alisa A.Vorobeva Zhaoxi Fang Panjun Sun Viktoriia M.Korzhuk Ilya Popov Zongda Wu Hamid Tahaei Institute of Artificial Intelligence Shaoxing UniversityShaoxing312000China Department of Computer Engineering Gonbad Kavous UniversityGonbad-e Kavus49717-99151Iran Faculty of Computer Engineering K.N.Toosi University of TechnologyTehran196976-4499Iran Department of Computer Science and Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesChennai602105India Secure Information Technologies Department National Research University ITMOSt.Petersburg197101Russia School of Electrical and Computer Engineering Shiraz UniversityShiraz71946–84334Iran Department of Computer Science and Engineering Islamic Azad UniversityDamavand***Iran Department of R&D Shenzhen BKD Co.Ltd.Shenzhen518000China

Software-Defined Networking(SDN)represents a significant paradigm shift in network architecture,separating network logic from the underlying forwarding devices to enhance flexibility and centralize ***-rently,the Internet of Things(IoT)connects numerous devices to the Internet,enabling autonomous interactions with minimal human ***,implementing and managing an SDN-IoT system is inherently complex,particularly for those with limited resources,as the dynamic and distributed nature of IoT infrastructures creates security and privacy challenges during SDN *** findings of this study underscore the primary security and privacy challenges across application,control,and data planes.A comprehensive review evaluates the root causes of these challenges and the defense techniques employed in prior works to establish sufficient secrecy and privacy *** investigations have explored cutting-edge methods,such as leveraging blockchain for transaction recording to enhance security and privacy,along with applying machine learning and deep learning approaches to identify and mitigate the impacts of Denial of Service(DoS)and Distributed DoS(DDoS)***,the analysis indicates that encryption and hashing techniques are prevalent in the data plane,whereas access control and certificate authorization are prominently considered in the control plane,and authentication is commonly employed within the application ***,this paper outlines future directions,offering insights into potential strategies and technological advancements aimed at fostering a more secure and privacy-conscious SDN-based IoT ecosystem.

关键词： Security privacy-preserving software-defined network internet of things

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Metaheuristic Secure Clustering Scheme for Energy Harvesting Wireless Sensor Networks

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computer Systems Science & engineering 2023年第4期45卷 497-512页

作者： S.Nithya Roopa P.Anandababu Sibi Amaran Rajesh Verma Department of Computer Science and Engineering Kumaraguru College of TechnologyCoimbatore641049India Department of Computer and Information Science Faculty of ScienceAnnamalai UniversityChidambaram608002India Department of Computing Technologies SRM Institute of Science and TechnologyChennai603203India Department of Electrical Engineering King Khalid UniversityAbha61411Kingdom of Saudi Arabia

Recently,energy harvesting wireless sensor networks(EHWSN)have increased significant attention among research *** harvesting energy from the neighboring environment,the sensors in EHWSN resolve the energy constraint problem and offers lengthened network *** is one of the proficient ways for accomplishing even improved lifetime in *** clustering process intends to appropriately elect the cluster heads(CHs)and construct *** several models are available in the literature,it is still needed to accomplish energy efficiency and security in *** this view,this study develops a novel Chaotic Rider Optimization Based Clustering Protocol for Secure Energy Harvesting Wireless Sensor Networks(CROC-SEHWSN)*** presented CROC-SEHWSN model aims to accomplish energy efficiency by clustering the node in *** CROC-SEHWSN model is based on the integration of chaotic concepts with traditional rider optimization(RO)***,the CROC-SEHWSN model derives a fitness function(FF)involving seven distinct parameters connected to *** accomplish security,trust factor and link quality metrics are considered in the *** design of RO algorithm for secure clustering process shows the novelty of the *** order to demonstrate the enhanced performance of the CROC-SEHWSN approach,a wide range of simulations are carried out and the outcomes are inspected in distinct *** experimental outcome demonstrated the superior performance of the CROC-SEHWSN technique on the recent approaches with maximum network lifetime of 387.40 and 393.30 s under two scenarios.

关键词： Clustering wireless sensor networks network lifetime energy efficiency metaheuristics energy harvesting rider optimization

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