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End-to-End Paired Ambisonic-Binaural Audio Rendering

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IEEE/CAA Journal of Automatica Sinica 2024年第2期11卷 502-513页

作者： Yin Zhu Qiuqiang Kong Junjie Shi Shilei Liu Xuzhou Ye Ju-Chiang Wang Hongming Shan Junping Zhang Shanghai Key Laboratory of Intelligent Information Processing School of Computer ScienceFudan UniversityShanghai 200433China Beijing ByteDance technology Co.Ltd. Shanghai 201102China. Chinese University of Hong Kong Hong KongChina IEEE institute of science and technology for brain-inspired intelligence and MOE Frontiers Center for brain science Fudan UniversityShanghai 200433 Shanghai Center for brain science and brain-inspired technology Shanghai 200031China

Binaural rendering is of great interest to virtual reality and immersive media. Although humans can naturally use their two ears to perceive the spatial information contained in sounds, it is a challenging task for machines to achieve binaural rendering since the description of a sound field often requires multiple channels and even the metadata of the sound sources. In addition, the perceived sound varies from person to person even in the same sound field. Previous methods generally rely on individual-dependent head-related transferred function(HRTF)datasets and optimization algorithms that act on HRTFs. In practical applications, there are two major drawbacks to existing methods. The first is a high personalization cost, as traditional methods achieve personalized needs by measuring HRTFs. The second is insufficient accuracy because the optimization goal of traditional methods is to retain another part of information that is more important in perception at the cost of discarding a part of the information. Therefore, it is desirable to develop novel techniques to achieve personalization and accuracy at a low cost. To this end, we focus on the binaural rendering of ambisonic and propose 1) channel-shared encoder and channel-compared attention integrated into neural networks and 2) a loss function quantifying interaural level differences to deal with spatial information. To verify the proposed method, we collect and release the first paired ambisonic-binaural dataset and introduce three metrics to evaluate the content information and spatial information accuracy of the end-to-end methods. Extensive experimental results on the collected dataset demonstrate the superior performance of the proposed method and the shortcomings of previous methods.

关键词： Ambisonic attention binaural rendering neural network

EmotionIC: emotional inertia and contagion-driven dependency modeling for emotion recognition in conversation

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science China(Information sciences) 2024年第8期67卷 130-146页

作者： Yingjian LIU Jiang LI Xiaoping WANG Zhigang ZENG School of Artificial intelligence and Automation Huazhong University of Science and Technology Hubei Key Laboratory of brain-inspired Intelligent Systems Huazhong University of Science and Technology Key Laboratory of Image Processing and Intelligent Control (Huazhong University of science and technology) Ministry of Education institute of Artificial intelligence Huazhong University of Science and Technology

Emotion recognition in conversation(ERC) has attracted growing attention in recent years as a result of the advancement and implementation of human-computer interface technologies. In this paper,we propose an emotional inertia and contagion-driven dependency modeling approach(EmotionIC) for ERC tasks. Our EmotionIC consists of three main components, i.e., identity masked multi-head attention(IMMHA), dialogue-based gated recurrent unit(DiaGRU), and skip-chain conditional random field(SkipCRF).Compared to previous ERC models, EmotionIC can model a conversation more thoroughly at both the feature-extraction and classification levels. The proposed model attempts to integrate the advantages of attention-and recurrence-based methods at the feature-extraction level. Specifically, IMMHA is applied to capture identity-based global contextual dependencies, while Dia GRU is utilized to extract speaker-and temporal-aware local contextual information. At the classification level, SkipCRF can explicitly mine complex emotional flows from higher-order neighboring utterances in the conversation. Experimental results show that our method can significantly outperform the state-of-the-art models on four benchmark *** ablation studies confirm that our modules can effectively model emotional inertia and contagion.

关键词： conditional random field emotion recognition in conversation emotional inertia and contagion gated recurrent unit multi-head attention

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Tuning the ferroelectricity of Hf0.5Zr0.5O2 with alloy electrodes

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science China(Information sciences) 2024年第8期67卷 321-330页

作者： Keqin LIU Bingjie DANG Zhiyu YANG Teng ZHANG Zhen YANG Jinxuan BAI Zelun PAN Ru HUANG Yuchao YANG Beijing Advanced Innovation Center for Integrated Circuits School of Integrated Circuits Peking University School of Electronic and Computer Engineering Peking University Center for brain inspired Chips Institute for Artificial Intelligence Peking University Center for brain inspired intelligence Chinese Institute for Brain ResearchBeijing

Tuning ferroelectricity of Hf0.5Zr0.5O2is crucial for facilitating its practical applications in various fields, including in-memory and neuromorphic computing. Previous studies have revealed that the electrodes have a significant influence on ferroelectricity, and changing electrode materials can realize different but discrete ferroelectric polarization values. Here, we introduce an alloy-electrode method, in order to achieve gradual and accurate modulation of ferroelectric polarization, especially useful for matching the polarization charges at the interface of ferroelectric insulators and ferroelectric semiconductors. Au and W electrodes are chosen as baselines for realizing weak and strong ferroelectric polarization, where the intermediate states can be achieved by adjusting the ratio of metals in the Au-W alloy. To demonstrate the generality of this approach, the Cu-W alloy electrode is also realized for tuning ferroelectric polarization. The effect of alloy electrodes on device leakage current, endurance, and retention is evaluated. In addition, the temperature stability of ferroelectric capacitors is tested, where limited changes in both remnant polarization and coercive voltages are observed, showing the great potential of the ferroelectric hafnium oxide. Such gradual modulation of ferroelectric polarization could facilitate the application of Hf0.5Zr0.5O2in in-memory and neuromorphic computing.

关键词： ferroelectric hafnium oxide alloy electrode gradual modulation temperature stability

Improving the electrical performances of InSe transistors by interface engineering

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Chinese Physics B 2024年第4期33卷 153-158页

作者：曹天俊郝松吴晨晨潘晨戴玉頔程斌梁世军缪峰 institute of brain-inspired intelligence National Laboratory of Solid State MicrostructuresSchool of PhysicsCollaborative Innovation Center of Advanced MicrostructuresNanjing UniversityNanjing 210093China institute of Interdisciplinary Physical sciences School of PhysicsNanjing University of Science and TechnologyNanjing 210014China

InSe has emerged as a promising candidate for next-generation electronics due to its predicted ultrahigh electrical ***,the efficacy of the InSe transistor in meeting application requirements is hindered due to its sensitivity to *** this study,we have achieved notable enhancement in the electrical performance of InSe transistors through interface *** engineered an InSe/h-BN heterostructure,effectively suppressing dielectric layer-induced ***,we successfully established excellent metal-semiconductor contacts using graphene ribbons as a buffer *** a methodical approach to interface engineering,our graphene/InSe/h-BN transistor demonstrates impressive on-state current,field-effect mobility,and on/off ratio at room temperature,reaching values as high as 1.1 mA/μm,904 cm^(2)·V^(-1)·s^(-1),and>10~6,*** computations corroborate that the graphene/InSe heterostructure shows significant interlayer charge transfer and weak interlayer interaction,contributing to the enhanced performance of InSe *** research offers a comprehensive strategy to elevate the electrical performance of InSe transistors,paving the way for their utilization in future electronic applications.

关键词： two-dimensional materials InSe van der Waals heterostructure electrical performances charge density difference

High precision current mirror circuit based on two-dimensional material transistors

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science China(Information sciences) 2024年第8期67卷 353-354页

作者： Shiping GAO Chen PAN Pincheng SU Xing-Jian YANGDONG Wentao YU Zhoujie ZENG Yu SHEN Jingwen SHI Yanwei CUI Pengfei WANG Yuekun YANG Cong WANG Bing CHENG Shi-Jun LIANG Feng MIAO institute of Interdisciplinary Physical sciences School of Physics Nanjing University of Science and Technology institute of brain-inspired intelligence National Laboratory of Solid State Microstructures School of PhysicsCollaborative Innovation Center of Advanced Microstructures

The emerging two-dimensional field-effect transistor(2DFET) is considered an important candidate device for driving future integrated circuit technology toward higher performance, lower power consumption, and more functionalities [1,2]. Among the integrated circuits, analog circuits play a crucial role as they are responsible for sampling, amplifying, and transmitting signals.

关键词： Timing circuits

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The Neural Mechanism of Knowledge Assembly in the Human brain Inspires Artificial intelligence Algorithm

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Neuroscience Bulletin 2024年第2期40卷 280-282页

作者： Xiang Ji Wentao Jiang Xiaoru Zhang Ming Song Shan Yu Tianzi Jiang University of the Chinese Academy of sciences Beijing 100049China brainnetome Center Institute of AutomationThe Chinese Academy of SciencesBeijing 100190China Laboratory of brain Atlas and brain-inspired intelligence Institute of AutomationThe Chinese Academy of SciencesBeijing 100190China CAS Center for Excellence in brain science and intelligence technology The Chinese Academy of SciencesBeijing 100190China Research Center for Augmented intelligence Zhejiang LabHangzhou 311100China

When new information enters the brain,a human's prior knowledge of the world can change rapidly through a process referred to as"knowledge assembly".Recently,Nelli et *** the neural correlates of knowledge assembly in the human brain using functional ***,inspired by the neural mechanism,the authors developed an artificial neural network algorithm to permit rapid knowledge assembly,improving the flexibility of the system[1].Once again,this research demonstrates that studying how the brain works can lead to better computational algorithms.

关键词： neural knowledge artificial

Toward understanding the role of genomic repeat elements in neurodegenerative diseases

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Neural Regeneration Research 2025年第3期20卷 646-659页

作者： Zhengyu An Aidi Jiang Jingqi Chen institute of science and technology for brain-inspired intelligence Fudan UniversityShanghaiChina MOE Frontiers Center for brain science Fudan UniversityShanghaiChina MOE Key Laboratory of Computational Neuroscience and brain-inspired intelligence Fudan UniversityShanghaiChina Zhangjiang Fudan International Innovation Center ShanghaiChina

Neurodegenerative diseases cause great medical and economic burdens for both patients and society;however, the complex molecular mechanisms thereof are not yet well understood. With the development of high-coverage sequencing technology, researchers have started to notice that genomic repeat regions, previously neglected in search of disease culprits, are active contributors to multiple neurodegenerative diseases. In this review, we describe the association between repeat element variants and multiple degenerative diseases through genome-wide association studies and targeted sequencing. We discuss the identification of disease-relevant repeat element variants, further powered by the advancement of long-read sequencing technologies and their related tools, and summarize recent findings in the molecular mechanisms of repeat element variants in brain degeneration, such as those causing transcriptional silencing or RNA-mediated gain of toxic function. Furthermore, we describe how in silico predictions using innovative computational models, such as deep learning language models, could enhance and accelerate our understanding of the functional impact of repeat element variants. Finally, we discuss future directions to advance current findings for a better understanding of neurodegenerative diseases and the clinical applications of genomic repeat elements.

关键词： Alzheimer's disease ataxia deep learning long-read sequencing neurodegeneration neurodegenerative diseases Parkinson's disease repeat element structural variant

Novel heterozygous USH1C mutation impacts hair cell mechanotransduction and causes progressive hearing loss

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science Bulletin 2024年第2期69卷 167-172页

作者： Yanyan Jia Gaogan Jia Luo Guo Nan Song Yu-Meng Wang Luoying Jiang Yilai Shu Yan Chen Shujia Zhu Huawei Li Wenyan Li ENT institute and Otorhinolaryngology Department of Eye&ENT Hospital State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain ScienceFudan UniversityShanghai 200031China institutes of Biomedical sciences Fudan UniversityShanghai 200032China NHC Key Laboratory of Hearing Medicine(Fudan University) Shanghai 200031China The institutes of brain science and the Collaborative Innovation Center for brain science Fudan UniversityShanghai 200032China Shanghai Center for brain science and brain-inspired intelligence technology Shanghai 201210China institute of Neuroscience State Key Laboratory of NeuroscienceCAS Center for Excellence in Brain Science and Intelligence TechnologyChinese Academy of SciencesShanghai 200031China Department of Cardiology and Institute for Developmental and Regenerative Cardiovascular MedicineXinhua Hospital Affiliated to Shanghai Jiaotong University School of MedicineShanghai 200092China

Hearing loss is one of the most common sensory disorders worldwide,affecting approximately 466 million people,including 34 million children[1].Genetic mutations accounts for approximately 60%of inherited hearing loss cases[2,3].These genetic changes result in a wide variety of clinical manifestations,ranging from nonsyndromic hearing loss(NSHL)to over 400 syndromes involving hearing loss and from mild adult-onset hearing loss to profound congenital deafness,covering the entire spectrum of Mendelian inheritance.

关键词： mec hearing approximate

Vector field path following for a micro flapping-wing robot

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science China(Information sciences) 2024年第6期67卷 442-444页

作者： Haifeng HUANG Yingte LIU Tao NIU Chang WANG Yao ZOU Wei HE School of intelligence science and technology University of Science and Technology Beijing institute of Artificial intelligence University of Science and Technology Beijing Key Laboratory of Intelligent Bionic Unmanned Systems Ministry of EducationUniversity of Science and Technology Beijing

Flapping-wing robots mimic the flight patterns of natural flying creatures,granting them natural *** hold promising applications in the military reconnaissance,urban surveillance,and various other fields[1–3].However,the current limitations in size often restrict the suitability of existing bird-like flapping-wing robots,

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