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31st International Conference on Computational Linguistics, COLING 2025

作者： Zhang, Chengwei Zhou, Yue Zhao, Rui Chen, Yidong Shi, Xiaodong School of Informatics Xiamen University China Key Laboratory of Digital Protection and Intelligent Processing of Intangible Cultural Heritage of Fujian and Taiwan Ministry of Culture and Tourism China Key Laboratory of Multimedia Trusted Perception and Efficient Computing Ministry of Education of China Xiamen University Xiamen China

ISBN: (纸本)9798891761964

Speech-to-text translation (ST) is a cross-modal task that involves converting spoken language into text in a different language. Previous research primarily focused on enhancing speech translation by facilitating knowledge transfer from machine translation, exploring various methods to bridge the gap between speech and text modalities. Despite substantial progress made, factors in speech that are not relevant to translation content, such as timbre and rhythm, often limit the efficiency of knowledge transfer. In this paper, we conceptualize speech representation as a combination of content-agnostic and content-relevant factors. We examine the impact of content-agnostic factors on translation performance through preliminary experiments and observe a significant performance deterioration when content-agnostic perturbations are introduced to speech signals. To address this issue, we propose a Speech Representation Purification with Supervision Enhancement (SRPSE) framework, which excludes the content-agnostic components within speech representations to mitigate their negative impact on ST. Experiments on MuST-C and CoVoST-2 datasets demonstrate that SRPSE significantly improves translation performance across all translation directions in three settings and achieves preeminent performance under a transcript-free setting. © 2025 Association for Computational Linguistics.

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A Novel Wide-Band High-Gain Microstrip Quasi-Yagi Antenna Design for X-Band Applications 5

A Novel Wide-Band High-Gain Microstrip Quasi-Yagi Antenna De...

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5th International Conference on Advances in Electrical, Electronics and Computing Technology, EECT 2025

作者： Wang, Xinju Wang, Sentao Chen, Zhuo Gan, Zongsheng Zhang, Haowei Yin, Yutong Liu, Lu Chen, Peng School of Ocean Information Engineering Jimei University Xiamen China School of Transportation and Civil Engineering Nantong University Nantong China School of Ocean Information Engineering Jimei University Fujian Provincial Key Laboratory of Maritime Communication and Intelligent Electronic Systems Fujian Provincial Key Laboratory of Oceanic Information Perception and Intelligent Processing Xiamen China

ISBN: (纸本)9798331541545

A new broadband high-gain microstrip quasi-yagi antenna is proposed. With the aim of designing an end-firing antenna for X-band by utilizing the good directivity of yagi antennas. The main radiating dipole patches of this antenna adopts an additional tapered trapezoidal-like structure to optimize its radiation characteristics. In addition, the operating bandwidth and main beam gain of the antenna are effectively adjusted by placing four identical microstrip metal strip patches on the bottom surface of the dielectric substrate to act as the reflector and the guide, respectively. Simulation results show that the designed antenna operates in the frequency bands of 8.33-13.07 GHz and 13.57-13.95 GHz with relative bandwidths of 44.3% and 2.76%, respectively, and achieves a peak gain of 8.9 dBi. The antenna has a simple structural design and is suitable for X-band wireless communication systems with a wide range of applications. © 2025 IEEE.

关键词： Microstrip antennas

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Colocalized Raman and IR Spectroscopies via Vibrational-Encoded Fluorescence for Comprehensive Vibrational Analysis

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Journal of the American Chemical Society 2025年第19期147卷 16309-16318页

作者： Meng, Zhao-Dong Wu, Tai-Rui Zhou, Li-Ling You, En-Ming Dong, Zhi-Peng Zhang, Xia-Guang Chen, Gan-Yu Wu, De-Yin Yi, Jun Tian, Zhong-Qun School of Electronic Science and Engineering State Key Laboratory of Physical Chemistry of Solid Surfaces College of Chemistry and Chemical Engineering Fujian Key Laboratory of Ultrafast Laser Technology and Applications IKKEM Xiamen University Xiamen361005 China School of Ocean Information Engineering Fujian Provincial Key Laboratory of Oceanic Information Perception and Intelligent Processing Jimei University Xiamen361021 China Key Laboratory of Green Chemical Media and Reactions Ministry of Education School of Chemistry and Chemical Engineering Henan Normal University Xinxiang453007 China

Vibrational spectroscopy, including Raman scattering and infrared (IR) absorption, provides essential molecular fingerprint information, facilitating diverse applications, such as interfacial sensing, chemical analysis, and biomedical diagnostics. The complementary selection rules of Raman and IR spectroscopies offer distinct, yet mutually reinforcing, insights into molecular structure and dynamics. However, in dynamic or complex chemical environments, either technique alone is not capable of providing a complete and nuanced picture of molecular vibrations. Simultaneous detection of complementary vibrational modes within the same molecular group remains challenging due to wavelength discrepancies and sensitivity mismatches between Raman and IR spectroscopies. In this work, to address the gap between these spectroscopies, we developed an integrated approach based on vibrational-encoded fluorescence (VEF), in which the complementary vibrational information is respectively encoded into the different parts of fluorescence radiation: Stokes fluorescence carrying Raman information and anti-Stokes fluorescence reflecting IR information. This method employs a dual-resonant microsphere-on-mirror plasmonic structure to bridge the waveband gap, enabling the simultaneous detection of complete vibrational modes in the visible spectrum with ultrahigh sensitivity down to ∼100 molecules. Hyperspectral colocalization imaging demonstrates spatial correlations between the complementary vibrations. By careful calibration, the detection efficiency is improved by 8 orders of magnitude compared to unenhanced IR spectroscopy. This approach creates new opportunities for the precise identification of molecular vibrational information in complex chemical environments. © 2025 American Chemical Society.

关键词： Vibrational spectroscopy

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Anchored Monotonic Alignment and Representation Substitution for Rare Spontaneous Behaviors in Spontaneous Speech Synthesis

Anchored Monotonic Alignment and Representation Substitution...

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

作者： Wu, Ning-Qian Hu, Ya-Jun Chen, Liping Ling, Zhen-Hua National Engineering Research Center of Speech and Language Information Processing University of Science and Technology of China Hefei China iFLYTEK Research iFLYTEK Co. Ltd. China MoE Key Laboratory of Brain-inspired Intelligent Perception and Cognition University of Science and Technology of China China

ISBN: (纸本)9798350368741

Spontaneous behaviors in speech pose significant challenges for speech synthesis. Existing research has not adequately addressed these behaviors, with most studies relying on specially recorded datasets. In contrast, real-world data more accurately reflects the natural, spontaneous speaking styles in everyday life and encompasses a wider range of spontaneous behaviors. However, such data is often of lower quality, and the distribution of spontaneous behaviors is highly imbalanced. In this study, we explore spontaneous speech synthesis using real-world data within the VITS2 framework. To overcome these challenges, we introduce two techniques: anchored monotonic alignment and spontaneous hidden representation substitution. Experimental results demonstrate that these methods enhance model alignment and improve the naturalness of the generated speech. Our proposed approach successfully addresses the challenge of synthesizing rare spontaneous behaviors and offers users flexible control over the synthesized speech. © 2025 IEEE.

关键词： real-world data speech synthesis spontaneous behaviors spontaneous speech synthesis VITS

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SNR improvement for Φ-OTDR with improved adaptive non-local means denoising method

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Optics Communications 2025年 587卷

作者： Zeng, Weiming Sun, Yizheng Shen, Hengwei Chen, Wen Liu, Jing Chen, Yushan Fan, Zhichun Fujian Provincial Key Laboratory of Oceanic Information Perception and Intelligent Processing School of Ocean Information Engineering Jimei University Xiamen361021 China

An improved adaptive non-local means (NLM) denoising method, called side window NLM (SW-NLM), was proposed in this study. Unlike the centrally symmetric square windows used in traditional NLM filtering, the SW-NLM method utilized rectangular side windows to further improve the signal-to-noise ratio (SNR) of phase-sensitive optical time domain reflectometer (Φ-OTDR). Additionally, SW-NLM method incorporated adaptive parameter estimation by calculating the SNR of the filtered traces and optimizing smoothing coefficients and window sizes accordingly. SW-NLM algorithm increased the SNR by up to 45.85 dB, achieving a 25.5% improvement over the NLM filtering while better preserving effective vibration information through the side window technique. Moreover, SW-NLM was applied to dual vibration condition to validate its capability of multipoint detection. This work contributes to enhancing the performance of Φ-OTDR and improving its signal recognition capability. © 2025 Elsevier B.V.

关键词： Image denoising

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Mid-infrared band multi-Fano resonance-based sensing of high-Q concave-convex arrays of metasurface with full control of Fano spectral profile

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Photonics and Nanostructures - Fundamentals and Applications 2025年 65卷

作者： Xu, Mengyang Lin, Dong Cai, Haoyuan Wang, Haoran Fan, Zhichun Liu, Jing Chen, Yushan School of Ocean Information Engineering Jimei University Xiamen361021 China Fujian Provincial Key Laboratory of Oceanic Information Perception and Intelligent Processing Jimei University Xiamen361021 China

In this study, a concave-convex array metasurface with a height difference characterized structure is proposed, combining in-plane and out-of-plane asymmetry to achieve a high Q-factor, refractive index sensing, and full control of the Fano spectral profile. Notably, both the concave model and the convex model, can only produce one Fano peak. But it can yield multiple Fano resonance peaks in the mid-infrared band following a simple combination. Herein, we have performed both near-field and far-field analysis for each Fano resonance generation. The designed metasurface achieves a remarkably high Q-factor of 9.63637 × 105. Moreover, it exhibits excellent reflection resonances under different polarization directions. In terms of refractive index sensing, the designed metasurface attains a sensitivity of 600 nm/RIU under TE polarization, while under TM polarization, it achieves full control of the Fano spectral profile by changing the incidence angle. The integration of periodic arrays with height differences in metasurfaces shows tremendous potential in controlling the Fano spectral profile and enhancing sensing capabilities. Additionally, this study will provide new inspirations for the sensing metasurface design with high optical performance. © 2025 Elsevier B.V.

关键词： Q factor measurement

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Geometry-Aware 3D Salient Object Detection Network

arXiv

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arXiv 2025年

作者： Wang, Chen Zhang, Liyuan Hui, Le Liu, Qi Dai, Yuchao Shaanxi Key Laboratory of Information Acquisition and Processing Northwestern Polytechnical University China PCA Lab Key Lab of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education Nanjing University of Science and Technology China

Point cloud salient object detection has attracted the attention of researchers in recent years. Since existing works do not fully utilize the geometry context of 3D objects, blurry boundaries are generated when segmenting objects with complex backgrounds. In this paper, we propose a geometry-aware 3D salient object detection network that explicitly clusters points into superpoints to enhance the geometric boundaries of objects, thereby segmenting complete objects with clear boundaries. Specifically, we first propose a simple yet effective superpoint partition module to cluster points into superpoints. In order to improve the quality of superpoints, we present a point cloud class-agnostic loss to learn discriminative point features for clustering superpoints from the object. After obtaining superpoints, we then propose a geometry enhancement module that utilizes superpoint-point attention to aggregate geometric information into point features for predicting the salient map of the object with clear boundaries. Extensive experiments show that our method achieves new state-of-the-art performance on the PCSOD dataset. Copyright © 2025, The Authors. All rights reserved.

关键词： Geometry

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EDSep: An Effective Diffusion-Based Method for Speech Source Separation

EDSep: An Effective Diffusion-Based Method for Speech Source...

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

作者： Dong, Jinwei Wang, Xinsheng Mao, Qirong School of Computer Science and Communication Engineering Jiangsu University China Jiangsu Engineering Research Center of Big Data Ubiquitous Perception and Intelligent Agriculture Applications China Provincial Key Laboratory of Computational Intelligence and New Technologies in Low-Altitude Digital Agriculture Zhenjiang China Audio Speech and Language Processing Group School of Computer Science Northwestern Polytechnical University Xi'an China

ISBN: (纸本)9798350368741

Generative models have attracted considerable attention for speech separation tasks, and among these, diffusion-based methods are being explored. Despite the notable success of diffusion techniques in generation tasks, their adaptation to speech separation has encountered challenges, notably slow convergence and suboptimal separation outcomes. To address these issues and enhance the efficacy of diffusion-based speech separation, we introduce EDSep, a novel single-channel method grounded in score matching via stochastic differential equation (SDE). This method enhances generative modeling for speech source separation by optimizing training and sampling efficiency. Specifically, a novel denoiser function is proposed to approximate data distributions, which obtains ideal denoiser outputs. Additionally, a stochastic sampler is carefully designed to resolve the reverse SDE during the sampling process, gradually separating speech from mixtures. Extensive experiments on databases such as WSJ0-2mix, LRS2-2mix, and VoxCeleb2-2mix demonstrate our proposed method's superior performance over existing diffusion and discriminative models, validating its efficacy. © 2025 IEEE.

关键词： diffusion score matching speech separation stochastic differential equation

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MCFNet: Multiscale Cross-domain Fusion Network for HSI and LiDAR Data Joint Classification

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IEEE Transactions on Geoscience and Remote Sensing 2025年 63卷

作者： Song, Qiya Mo, Feng Ding, Kexin Xiao, Lin Dian, Renwei Kang, Xudong Li, Shutao Hunan Normal University School of Information Science and Engineering Hunan Changsha410081 China School of Robotics Hunan University Hunan Changsha410082 China Fujian Key Laboratory of Spatial Information Perception and Intelligent Processing Yango University China

Hyperspectral image (HSI) encompasses abundant spatial and spectral details, while Light Detection and Ranging (LiDAR) delivers precise elevation data. The amalgamation of HSI and LiDAR data significantly improves the precision of image classification. However, most methods focus solely on spatial features while neglecting frequency domain information, limiting the ability of deep models to characterize land cover. Furthermore, how to establish a sufficient interaction between different modalities is also an important issue. In this paper, we propose a novel multiscale cross-domain fusion network (MCFNet) for joint classification of HSI and LiDAR data. The main idea is that the wavelet transform can provide details at different resolutions simultaneously, supplementing spatial domain information and enriching feature representation. In addition, the multimodal fusion module (MFM) guided by HSI and the cross-domain fusion module (CDFM) strategy are developed to integrate features from diverse modalities and domains, respectively. Specifically, frequency domain features are extracted by discrete wavelet transform, and spatial domain features of the image are captured through a set of convolution operations. Then interactive fusion is performed by MFM and CDFM, and finally the integrated features are categorized using a classification module. Extensive experiments on three widely-used HSI and LiDAR datasets indicate that MCFNet outperforms the SOTA methods. © 1980-2012 IEEE.

关键词： Frequency domain analysis

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Molecular dynamics simulation of heat transfer during liquid hydrogen boiling on surfaces at the nanoscale

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Nuclear Science and Techniques 2025年第7期36卷 1-12页

作者： Li, Xiao-Jia Chen, He-Ying Sun, Yi-Zheng Fan, Zhi-Chun School of Ocean Information Engineering Jimei University Xiamen361021 China Department of Mechanical Engineering City University of Hong Kong Hong Kong Fujian Provincial Key Laboratory of Oceanic Information Perception and Intelligent Processing Jimei University Xiamen361021 China

Liquid hydrogen, known for its high energy density and eco-friendly properties, has garnered significant attention in the context of sustainable development and clean energy. A comprehensive understanding of its nucleation mechanisms and boiling heat transfer characteristics is crucial. However, current experimental and macroscopic simulation methods offer limited insights. This study employs molecular dynamics simulations to investigate the vaporization nucleation and boiling heat transfer properties of liquid hydrogen at the microscopic scale, with a focus on the effects of hydrogen film thickness, surface temperature, and wettability. The results indicate that hydrogen film thickness plays a critical role in nucleation. Thinner layers disrupt the shape of liquid films, leading to increased errors, whereas a thickness of 7 nm ensures film stability. Different heating methods and temperatures influence nucleation in various ways. Rapid heating results in a higher heat flux, while an increase in temperature under the same heating method accelerates nucleation, resulting in earlier nucleation and enhanced surface heat flow. Surfaces with varying wettability levels exhibit distinct nucleation behaviors. Specifically, an increase in α delays nucleation, causing a shift from the surface to within the liquid film due to stronger solid–liquid interaction forces. This study offers a microscale perspective on the nucleation and boiling processes of liquid hydrogen and provides valuable insights for phase transition studies. © The Author(s), under exclusive licence to China Science Publishing & Media Ltd. (Science Press), Shanghai Institute of Applied Physics, the Chinese Academy of Sciences, Chinese Nuclear Society 2025.

关键词： Electric heating

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