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Suno:potential,prospects,and trends

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Frontiers of Information Technology & Electronic Engineering 2024年第7期25卷 1025-1030页

作者： Jiaxing YU Songruoyao WU Guanting LU Zijin LI Li ZHOU Kejun ZHANG College of Computer Science and Technology Zhejiang UniversityHangzhou 310027China Department of music Artificial Intelligence and music Information Technology Central Conservatory of MusicBeijing 100031China school of Arts and Communication China University of Geosciences(Wuhan)Wuhan 430074China Innovation Center of Yangtze River Delta Zhejiang UniversityJiaxing 314100China

Suno has attracted wide attention due to its impressive *** demonstrates technological advancements and opens up new possibilities for music composition,representing a milestone in the development of artificial intelligence(AI)music gen*** this paper,we first introduce the background and summarize the general technical framework of AI music generation,followed by an analysis of Suno’s advantages and ***,we discuss the future trends in music and AI.

关键词： potential representing artificial

Recent advances in artificial intelligence generated content

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Frontiers of Information Technology & Electronic Engineering 2024年第1期25卷 1-5页

作者： Junping ZHANG Lingyun SUN Cong JIN Junbin GAO Xiaobing LI Jiebo LUO Zhigeng PAN Ying TANG Jingdong WANG school of Computer Science Fudan UniversityShanghai 200433China International Design Institute Zhejiang UniversityHangzhou 310058China school of Information and Communication Engineering Communication University of ChinaBeijing 100024China The University of Sydney Business school The University of SydneyNSW 2006Australia Department of AI music and music Information Technology Central Conservatory of MusicBeijing 100032China Department of Computer Science University of RochesterNY 14627USA school of Artificial Intelligence Nanjing University of Information Science and TechnologyNanjing 210044China Electrical and Computer Engineering Department Rowan UniversityGlassboroNJ 08028USA Baidu Beijing 100085China

Artificial intelligence generated content(AIGC)has been a research hotspot in the field of artificial intelligence in recent *** is expected to replace humans in performing some of the work of content generation at a low cost and a high volume,such as music,painting,multimodal content generation,news articles,summary reports,stock commentary summaries,and even content and digital people generated in the *** provides a new technical path for the development and implementation of AI in the future.

关键词： artificial replace content

Study on the Influence of AI Composition Software on Students'Creative Ability in music Education

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教育技术与创新 2024年第2期6卷 1-17页

作者： Shuang Zhang Xiaofeng Lu Xinwen Liu school of music Wenzhou UniversityChina Business school of Wenzhou University China school of Fine Arts and Design Wenzhou UniversityChina

Generative AI technology for human-assisted tools has made great strides in recent years,and studying the impact of this technology on students'compositional abilities plays an important role in promoting changes in music *** studies have focused on the performance of music composition software itself in terms of composition,with less consideration given to the impact of creators'compositional ability after using assistive composition ***,this paper designs a controlled experiment to investigate the changes in students'compositional ability before and after using AI composition *** paper finds that students'compositional abilities in all areas of composition improved to varying degrees after using AI composition *** paper compares the differences in compositional abilities of students with and without the education of AI composition tools,which has practical implications for vigorously promoting the adoption of AI composition tools in university music education teaching.

关键词： music Education AI Composition Composition Ability Assessment

Detecting somatisation disorder via speech:introducing the Shenzhen Somatisation Speech Corpus

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Intelligent Medicine 2024年第2期4卷 96-103页

作者： Kun Qian Ruolan Huang Zhihao Bao Yang Tan Zhonghao Zhao Mengkai Sun Bin Hu Björn W.Schuller Yoshiharu Yamamoto Key Laboratory of Brain Health Intelligent Evaluation and Intervention Ministry of EducationBeijing Institute of TechnologyBeijing 100081China school of Medical Technology Beijing Institute of TechnologyBeijing 100081China The First school of Clinical Medicine Southern Medical UniversityGuangzhouGuangdong 510515China Department of Neurology Shenzhen University General HospitalShenzhenGuangdong 518055China Group on Language Audio&MusicImperial College LondonLondon SW72AZUK Embedded Intelligence for Health Care and Wellbeing University of AugsburgAugsburg 86159Germany Educational Physiology Laboratory Graduate School of EducationThe University of TokyoTokyo 113-0033Japan

Objective Speech recognition technology is widely used as a mature technical approach in many *** the study of depression recognition,speech signals are commonly used due to their convenience and ease of *** speech recognition is popular in the research field of depression recognition,it has been little studied in somatisation disorder *** reason for this is the lack of a publicly accessible database of relevant speech and benchmark *** this end,we introduced our somatisation disorder speech database and gave benchmark *** By collecting speech samples of somatisation disorder patients,in cooperation with the Shenzhen University General Hospital,we introduced our somatisation disorder speech database,the Shenzhen Somatisation Speech Corpus(SSSC).Moreover,a benchmark for SSSC using classic acoustic features and a machine learning model was proposed in our *** To obtain a more scientific benchmark,we compared and analysed the performance of different acoustic features,i.e.,the full ComPare feature set,or only Mel frequency cepstral coefficients(MFCCs),fundamental frequency(F0),and frequency and bandwidth of the formants(F1-F3).By comparison,the best result of our benchmark was the 76.0%unweighted average recall achieved by a support vector machine with formants F1–*** The proposal of SSSC may bridge a research gap in somatisation disorder,providing researchers with a publicly accessible speech *** addition,the results of the benchmark could show the scientific validity and feasibility of computer audition for speech recognition in somatization disorders.

关键词： Somatisation disorder Machine learning Healthcare Computer audition

Wearable and interactive multicolored photochromic fiber display

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Light(Science & Applications) 2024年第3期13卷 454-465页

作者： Pan Li Yuwei Wang Xiaoxian He Yuyang Cui Jingyu Ouyang Ju Ouyang Zicheng He Jiayu Hu Xiaojuan Liu Hang Wei Yu Wang Xiaoling Lu Qian Ji Xinyuan Cai Li Liu Chong Hou Ning Zhou Shaowu Pan Xiangru Wang Huamin Zhou Cheng-Wei Qiu Yan-Qing Lu Guangming Tao State Key Laboratory of Material Processing and Die&Mould Technology School of Materials Science and Engineering and Wuhan National Laboratory for OptoelectronicsHuazhong University of Science and TechnologyWuhan 430074China Key Laboratory of Vascular Aging(HUST) Ministry of EducationWuhan 430030China school of Optoelectronic Science and Engineering University of Electronic Science and Technology of ChinaChengdu 611731China Department of Electrical and Computer Engineering National University of SingaporeSingapore 117583Singapore National Laboratory of Solid State Microstructures Key Laboratory of Intelligent Optical Sensing and ManipulationCollege of Engineering and Applied Sciencesand Collaborative Innovation Center of Advanced MicrostructuresNanjing UniversityNanjing 210023China school of Performing Arts Wuhan Conservatory of MusicWuhan 430060China school of Mechanical Science and Engineering Huazhong University of Science and TechnologyWuhan 430074China school of Architecture and Urban Planning Huazhong University of Science and TechnologyWuhan 430074China school of Fashion Beijing Institute of Fashion TechnologyBeijing 100029China school of Optical and Electronic Information Huazhong University of Science and TechnologyWuhan 430074China Tongji Medical College Huazhong University of Science and TechnologyWuhan 430074China State Key Laboratory for Modification of Chemical Fibers and Polymer Materials College of Materials Science and EngineeringDonghua UniversityShanghai 201620China

Endowing flexible and adaptable fiber devices with light-emitting capabilities has the potential to revolutionize the current design philosophy of intelligent,wearable interactive ***,significant challenges remain in developing fiber devices when it comes to achieving uniform and customizable light effects while utilizing lightweight ***,we introduce a mass-produced,wearable,and interactive photochromic fiber that provides uniform multicolored light *** designed independent waveguides inside the fiber to maintain total internal reflection of light as it traverses the *** impact of excessive light leakage on the overall illuminance can be reduced by utilizing the saturable absorption effect of fluorescent materials to ensure light emission uniformity along the transmission *** addition,we coupled various fluorescent composite materials inside the fiber to achieve artificially controllable spectral radiation of multiple color systems in a single *** prepared fibers on mass-produced kilometer-long using the thermal drawing *** fibers can be directly integrated into daily wearable devices or clothing in various patterns and combined with other signal input components to control and display patterns as *** work provides a new perspective and inspiration to the existing field of fiber display interaction,paving the way for future human–machine integration.

关键词： fiber interactive colored

Rapid Phase Ambiguity Elimination Methods for DOA Estimator via Hybrid Massive MIMO Receive Array

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Chinese Journal of Electronics 2024年第1期33卷 175-184页

作者： Xichao ZHAN Zhongwen SUN Feng SHU Yiwen CHEN Xin CHENG Yuanyuan WU Qi ZHANG Yifan LI Peng ZHANG school of Information and Communication Engineering Hainan University school of Electronic and Optical Engineering Nanjing University of Science and Technology

For a sub-connected hybrid multiple-input multiple-output(MIMO) receiver with K subarrays and N antennas, there exists a challenging problem of how to rapidly remove phase ambiguity in only single time-slot. A direction of arrival(DOA) estimator of maximizing received power(Max-RP) is proposed to find the maximum value of K-subarray output powers, where each subarray is in charge of one sector, and the center angle of the sector corresponding to the maximum output is the estimated true DOA. To make an enhancement on precision, Max-RP plus quadratic interpolation(Max-RP-QI) method is designed. In the proposed Max-RP-QI, a quadratic interpolation scheme is adopted to interpolate the three DOA values corresponding to the largest three receive powers of *** achieve the Cramer Rao lower bound, a Root-music plus Max-RP-QI scheme is developed. Simulation results show that the proposed three methods eliminate the phase ambiguity during one time-slot and also show low computational complexities. The proposed Root-music plus Max-RP-QI scheme can reach the Cramer Rao lower bound,and the proposed Max-RP and Max-RP-QI are still some performance losses 2–4 d B compared to the Cramer Rao lower bound.

关键词： Phased arrays Interpolation Wireless sensor networks Direction-of-arrival estimation Simulation Receiving antennas Massive MIMO

Cogeneration of Innovative Audio-visual Content: A New Challenge for Computing Art

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Machine Intelligence Research 2024年第1期21卷 4-28页

作者： Mengting Liu Ying Zhou Yuwei Wu Feng Gao Advanced Institute of Information Technology Peking UniversityHangzhou311215China school of Electronic and Computer Engineering Shenzhen Graduate SchoolPeking UniversityShenzhen 518000China Peng Cheng Laboratory Shenzhen 518000China school of Arts Peking UniversityBeijing 100871China

In recent years,computing art has developed rapidly with the in-depth cross study of artificial intelligence generated con-tent(AIGC)and the main features of ***-visual content generation has gradually been applied to various practical tasks,including video or game score,assisting artists in creation,art education and other aspects,which demonstrates a broad application *** this paper,we introduce innovative achievements in audio-visual content generation from the perspective of visual art genera-tion and auditory art generation based on artificial intelligence(Al).We outline the development tendency of image and music datasets,visual and auditory content modelling,and related automatic generation *** objective and subjective evaluation of generated samples plays an important role in the measurement of algorithm *** provide a cogeneration mechanism of audio-visual content in multimodal tasks from image to music and display the construction of specific stylized *** are still many new op-portunities and challenges in the field of audio-visual synesthesia generation,and we provide a comprehensive discussion on them.

关键词： Artificial intelligence(AI)art audio-visual artificial intelligence generated content(AIGC) multimodal artistic evalu-ation

Style-conditioned music generation with Transformer-GANs

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Frontiers of Information Technology & Electronic Engineering 2024年第1期25卷 106-120页

作者： Weining WANG Jiahui LI Yifan LI Xiaofen XING school of Electronic and Information Engineering South China University of TechnologyGuangzhou 510600China

Recently,various algorithms have been developed for generating appealing ***,the style control in the generation process has been somewhat *** style refers to the representative and unique appearance presented by a musical work,and it is one of the most salient qualities of *** this paper,we propose an innovative music generation algorithm capable of creating a complete musical composition from scratch based on a specified target style.A style-conditioned linear Transformer and a style-conditioned patch discriminator are introduced in the *** style-conditioned linear Transformer models musical instrument digital interface(MIDI)event sequences and emphasizes the role of style ***,the style-conditioned patch discriminator applies an adversarial learning mechanism with two innovative loss functions to enhance the modeling of music ***,we establish a discriminative metric for the first time,enabling the evaluation of the generated music’s consistency concerning music *** objective and subjective evaluations of our experimental results indicate that our method’s performance with regard to music production is better than the performances encountered in the case of music production with the use of state-of-the-art methods in available public datasets.

关键词： music generation Style-conditioned Transformer music emotion

musicFace: music-driven expressive singing face synthesis

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Computational Visual Media 2024年第1期10卷 119-136页

作者： Pengfei Liu Wenjin Deng Hengda Li Jintai Wang Yinglin Zheng Yiwei Ding Xiaohu Guo Ming Zeng school of Informatics Xiamen UniversityXiamen361000China Department of Computer Science The University of Texas at DallasRichardsonTexas75080-3021USA

It remains an interesting and challenging problem to synthesize a vivid and realistic singing face driven by music. In this paper, we present a method for this task with natural motions for the lips, facial expression, head pose, and eyes. Due to the coupling of mixed information for the human voice and backing music in common music audio signals, we design a decouple-and-fuse strategy to tackle the challenge. We first decompose the input music audio into a human voice stream and a backing music stream. Due to the implicit and complicated correlation between the two-stream input signals and the dynamics of the facial expressions, head motions, and eye states, we model their relationship with an attention scheme, where the effects of the two streams are fused seamlessly. Furthermore, to improve the expressivenes of the generated results, we decompose head movement generation in terms of speed and direction, and decompose eye state generation into short-term blinking and long-term eye closing, modeling them separately. We have also built a novel dataset, SingingFace, to support training and evaluation of models for this task, including future work on this topic. Extensive experiments and a user study show that our proposed method is capable of synthesizing vivid singing faces, qualitatively and quantitatively better than the prior state-of-the-art.

关键词： face synthesis singing music generative adversarial network