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Semantic Analysis and Modeling of the Color of Stage Costume – A Case Study of “The Painting Journey”

Semantic Analysis and Modeling of the Color of Stage Costume...

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Culture-Oriented Science and technology (CoST), International Conference on

作者： Wenli Huang Bowen Liu Fang Sun Shuang Wang State Key Laboratory of Media Convergence and Communication Communication University of China China Key Laboratory of Acoustic Visual Technology and Intelligent Control System (Communication University of China) China Beijing Key Laboratory of Modern Entertainment Technology (Communication University of China) China

ISBN: (数字)9798350380347

ISBN: (纸本)9798350380354

The creation of Chinese dance dramas plays an important role in the dissemination of Chinese culture in the context of pluralistic unity. As one of the outstanding poetry dramas in the past two years, “The Journey of a Legendary Landscape Painting” (JLLP) has rich national cultural connotations and aesthetic value in its stage costume colors. This article first studied the data extraction method of stage costume colors based on clustering and association rule mining, and constructed the color dataset for JLLP. On this basis, the color semantic mining and extraction including subjective and objective factors were conducted. Finally, combined with color semantics, the character personality of JLLP was further analyzed. The research results show that the color extraction method designed in this article can accurately preserve the color characteristics of stage costumes. In addition, the costume colors of JLLP play a good supporting role in shaping the character personality.

关键词： Humanities Costs Correlation Image color analysis Databases Semantics Clustering algorithms

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Research on Named Entity Recognition for Oral History Text

Research on Named Entity Recognition for Oral History Text

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Culture-Oriented Science and technology (CoST), International Conference on

作者： Chaoyu Hu Shilei Bai Mengfei Zhang School of Information and Communication Engineering Communication University of China Beijing China Beijing Key Laboratory of Modern Entertainment Technology Beijing China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture Beijing China

ISBN: (数字)9798350380347

ISBN: (纸本)9798350380354

Oral history involves conveying experienced events through spoken narratives, typically preserved and later studied by converting spoken language into text. Named entity recognition (NER) is the recognition of meaningful named entities in text, such as person names, locations, organizations, etc. Conducting NER research on oral history text is significant as it not only facilitates the verification of named entities by researchers but also allows for the extraction of key information from texts through named entities. By collecting oral history corpus, we establish an oral history text dataset, manually annotating all texts with six entity labels and repeatedly verifying them manually. Utilizing the concept of machine reading comprehension (MRC), a semantic fusion module was added, integrating label information into text information using a cross-attention mechanism, and decoding the corresponding entity labels through span decoding. The final model performs well on the oral history text dataset and also showed good performance on general Chinese datasets.

关键词： Costs Text recognition Semantics Named entity recognition Organizations Decoding History

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The Algorithm of Sequential Music Recommendation Based on BERT

The Algorithm of Sequential Music Recommendation Based on BE...

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Culture-Oriented Science and technology (CoST), International Conference on

作者： Zhen Li Kaiyue Li Qingqing Yang State Key Laboratory of Media Convergence of Communication Key Laboratory of Acoustic Visual Technology and Intelligent Control System (Communication University of China) Ministry of Culture and Tourism Beijing Key Laboratory of Modern Entertainment Technology Communication University of China Communication University of China Beijing China

Music recommendation algorithms aim to predict the songs that users might be interested in based on various factors, such as their listening history. The best existing method is Bert_Music, a sequential music recommendation model based on Bidirectional Encoder Representation from Transformer (BERT). This model leverages user sequence context information to improve recommendation performance. However, Bert_Music only considers the sequence information of songs and ignores their content characteristics. To address this limitation, we propose an improved version of Bert_Music, which is a sequential music recommendation model based on Bidirectional Encoder Representation from Transformer with tag information (BERT_MUSIC_T), uses song ID (Identity) and tag information to make more accurate recommendations. We compared the performance of Bert_Music_T with that of the Bert_Music model on the *** dataset and found that the Precision has increased by up to 2.85%. These results prove the validity of our method.

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Research on Hybrid Path Planning Algorithm Based on Anti-Collision

Research on Hybrid Path Planning Algorithm Based on Anti-Col...

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Culture-Oriented Science and technology (CoST), International Conference on

作者： Penghao Ren Mengnan Li Zhibin Su Beijing Radio & Television Station Beijing China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture and Tourism Communication University of China Beijing Key Laboratory of Modern Entertainment Technology Communication University of China Beijing China

In order to solve the problem of fast switching of special equipment in the cultural complex, the improved Moth-Flame Optimization algorithm (MFO) is combined with the improved Dynamic Window Approach (DWA) to realize the hybrid path planning of handling robots in different scenarios of cultural complexes in this paper. Specifically, the traditional Moth-Flame Optimization algorithm is improved and applied to the global path planning problem. On the basis of the planned global path, the intersection of dynamic obstacles with the global path is detected, and the improved Dynamic Window Approach is used for local obstacle avoidance in the section with collision risk, finally, the hybrid path planning in the complex environment of the cultural complex is realized. The simulation experimental results prove the effectiveness of the proposed algorithm.

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Source Separation of Piano Concertos Using Hybrid LSTM-Transformer Model

Source Separation of Piano Concertos Using Hybrid LSTM-Trans...

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Culture-Oriented Science and technology (CoST), International Conference on

作者： JingYu Liu Wei He Jingjing Zhou Wei Jiang State Key Laboratory of Media Convergence and Communication Beijing China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture and Tourism Beijing China School of Information and Communication Engineering (Communication University of China) Beijing China

ISBN: (数字)9798350380347

ISBN: (纸本)9798350380354

Music source separation, the process of extracting independent audio streams from a complex mix, has traditionally focused on isolating vocals, drums, bass, and other primary sources. This study tackles the more intricate task of separating the piano component from a piano concerto-a challenge compounded by the diverse range of instruments and the dynamic shifts in volume and timbre. Unlike traditional music separation tasks, the piano’s distinct characteristics and its interaction with the orchestra demand a more nuanced *** address the scarcity of multi-track recordings for piano concertos, this research pioneers an artificial data synthesis strategy to create a robust training dataset. We introduce a novel hybrid deep learning model that integrates Long Short-Term Memory (LSTM) networks with Transformer architecture, capitalizing on their complementary strengths to distinguish piano melodies from the rich tapestry of orchestral sounds. Our experiments demonstrate that this hybrid approach significantly outperforms conventional methods, with an improvement of 3.18 dB in signal-to-distortion ratio. These results not only validate the efficacy of proposed method but also pave the way for innovative applications in classical music source separation.

关键词： Training Deep learning Source separation Instruments Transformers Recording Timbre

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Study on the classification of beatbox sounds based on timbre features

Study on the classification of beatbox sounds based on timbr...

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Culture-oriented Science & technology (ICCST), International Conference on

作者： Jiaxing Zhu Junping Wang Jingyu Liu Xiaoyi Zhang Conservatory of Music Key Laboratory of Acoustic Visual Technology and Intelligent Control System (Communication University of China) Ministry of Culture and Tourism Beijing Key Laboratory of Modern Entertainment Technology Communication University of China School of Information and Communication Engineering Communication University of China Beijing China

ISBN: (数字)9781728181387

ISBN: (纸本)9781728181394

Beatbox is a performance form of vocal percussion, which is gradually favored by people with continuous development in recent years. With the abundance of Beatbox content on the Internet, the research on its automatic classification becomes very significant. In this article, we mainly using machine learning methods, to identify the beatbox timbre. First of all, we collected 900 Beatbox audio materials and constructed a database. Secondly, 14 acoustic parameters of audio material are extracted by the signal processing method. Finally, we used MultilayerPerceptron, SMO, BayesNet, RandomForest in current machine learning to build a training model for BB timbre classification. The Experimental results showed that the model could classify BB timbre well.

关键词： Timbre Classification algorithms Machine learning algorithms acoustics Music Training Signal processing algorithms

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Design and Implementation of an Linkage Control system for Stage visual Effect Equipment

Design and Implementation of an Linkage Control System for S...

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Culture-oriented Science & technology (ICCST), International Conference on

作者： Shilei Bai Yihan Suo Kai Xu Xiujun Tang Jiaxin Zhang School of Information and Communication Engineering Communication University of China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture and Tourism (Communication University of China) Beijing Key Laboratory of Modern Entertainment Technology (Communication University of China) State Key Laboratory of Media Convergence of Communication Beijing China

ISBN: (数字)9781728181387

ISBN: (纸本)9781728181394

In view of the problems of low equipment integration, difficult equipment operation, and high technical threshold existing in the current stage visual effect linkage control system, a highly integrated linkage control system for stage visual effect equipment, which is suitable for small and medium-sized performance venues, is proposed in this paper. This system can control the stage lighting and the playback of multi-channel and multi-format media content, and it is easy to control. The design scheme of the system is described in detail, and the feasibility of the system is verified through tests in this paper.

关键词： visual effects Lighting Couplings Control systems Libraries Software Process control

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Classification of Dunhuang Mural Image Based on Small-sample and Semi-supervised Learning

Classification of Dunhuang Mural Image Based on Small-sample...

引用

IEEE Information technology, Networking, Electronic and Automation Control Conference

作者： Hui Cui Zhibin Su Luyue Zhang Liyang Bai School of Information and Engineering Communication University of China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Center for Ethnic and Folk Literature and Art Development Ministry of Culture and Tourism P.R.C.

Dunhuang mural images classification belongs to the research task in the field of image recognition. In this paper, the semi-supervised model is established with multidimensional features extracted by transfer learning. A small number of labeled samples were used to obtain a large number of unlabeled data, combined with Active Learning and iterative strategy for multiple rounds of label transfer of selected samples. After several rounds of iterations, we can get a more powerful classification learner. Experiments on the self-built Dunhuang mural dataset have shown that the results can approach or even exceed some supervised learning methods when the number of known label samples is less than 4%. Our research implements the cultural resource image classification algorithm based on small samples, which is conductive to improving the accuracy when label samples are scarce.

关键词： Technological innovation Transfer learning Supervised learning Semisupervised learning Predictive models Feature extraction Classification algorithms

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Joint Depth Estimation and Semantic Segmentation with Adversarial Multi-task Network

Joint Depth Estimation and Semantic Segmentation with Advers...

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Culture-oriented Science & technology (ICCST), International Conference on

作者： Hui Ren Nan Gao Jia Li State Key Laboratory of Media Convergence of Communication Communication University of China Beijing China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Communication University of China Beijing China School of Information and Communication Engineering Communication University of China Beijing China

ISBN: (数字)9781728181387

ISBN: (纸本)9781728181394

Some exiting works have explored the promotion between depth estimation and semantic segmentation. These works are usually based on convolutional neural networks, which extract compact features and map the relationship between input and output according to specific tasks. In this paper, we introduce a novel adversarial training strategy, that is, generator produces the semantic segmentation map and depth map, and then the discriminator can judge the authenticity of the synthesized color image, thereby supervising the output of the network during back propagation. We use the adversarial loss combined with the reconstruction loss function to supervise the model, and find that the adversarial loss function which is seen as a global supervision can further optimize the output. We use 200 color images from Kitti dataset with semantic segmentation ground truth as the training set, and train the network in an end-to-end manner. The experimental results show that the adversarial training method is well applied to the multi-task training combining semantic segmentation and depth estimation, and can further improve the quantitative performance of depth estimation.

关键词： Semantics Estimation Generative adversarial networks Generators Training Task analysis Mathematical model

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Association Between Timbre Perception Features and Fine-Grained Emotions in Film and Television Music

Association Between Timbre Perception Features and Fine-Grai...

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Culture-Oriented Science and technology (CoST), International Conference on

作者： Xiaomeng Ren Zhibin Su Wei Jiang Jingyu Liu State Key Laboratory of Media Convergence and Communication (Communication University of China) China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture and Tourism (Communication University of China) China School of Information and Communication Engineering (Communication University of China) China

ISBN: (数字)9798350380347

ISBN: (纸本)9798350380354

As an integral component of modern cultural works, the role of film and television music in artistic expression and emotional communication has become increasingly significant. Timbre, as a crucial attribute of music, has primarily been studied in terms of the influence of its fundamental objective parameters on coarse-grained emotions. However, there is a lack of in-depth exploration of the association between timbre perception features and fine-grained emotion. Consequently, this paper approaches from the perspective of timbre perception features and fine-grained emotions in film and television music. By conducting perceptual evaluation and subjective emotional annotation experiments, it analyzes the correlation between timbre perception features and fine-grained emotions, confirming that timbre perception features significantly influence musical emotions. Furthermore, a multivariate linear regression model was employed to construct a fine-grained emotion prediction model, which has demonstrated good predictive ability for most musical emotions. This research provides a new perspective on understanding the relationship between timbre and emotion in film and television music, offering a scientific basis for its creation and performance.

关键词： TV Costs Correlation Annotations Linear regression Predictive models Timbre

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