检索结果-南通市图书馆

Dance2MIDI:Dance-driven multi-instrument music generation

Computational Visual Media 2024年第4期10卷 791-802页

作者： Bo Han Yuheng Li Yixuan Shen Yi Ren Feilin Han College of Computer Science and Technology Zhejiang UniversityHangzhou 310058China National University of Singapore Singapore 119077Singapore Speech&Audio Team Bytedance AI LabSingapore 048583Singapore Department of Film and TV Technology Beijing Film AcademyBeijing 100088China

Dance-driven music generation aims to generate musical pieces conditioned on dance *** works focus on monophonic or raw audio generation,while the multi-instrument scenario is *** challenges associated with dancedriven multi-instrument music(MIDI)generation are twofold:(i)lack of a publicly available multi-instrument MIDI and video paired dataset and(ii)the weak correlation between music and *** tackle these challenges,we have built the first multi-instrument MIDI and dance paired dataset(D2MIDI).Based on this dataset,we introduce a multi-instrument MIDI generation framework(Dance2MIDI)conditioned on dance ***,to capture the relationship between dance and music,we employ a graph convolutional network to encode the dance *** allows us to extract features related to dance movement and dance ***,to generate a harmonious rhythm,we utilize a transformer model to decode the drum track sequence,leveraging a cross-attention ***,we model the task of generating the remaining tracks based on the drum track as a sequence understanding and completion task.A BERTlike model is employed to comprehend the context of the entire music piece through self-supervised *** evaluate the music generated by our framework trained on the D2MIDI dataset and demonstrate that our method achieves state-of-the-art performance.

关键词： video understanding music generation symbolic music cross-modal learning self-supervision

来源：

维普期刊数据库评论

在线全文

维普期刊数据库

学校读者我要写书评

暂无评论

Style-conditioned music generation with Transformer-GANs

引用

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

来源：

维普期刊数据库

同方期刊数据库评论

在线全文

学校读者我要写书评

暂无评论

Structured music Transformer: Structured conditional music generation based on stylistic clustering using Transformer

Structured Music Transformer: Structured conditional music g...

引用

第43届中国控制会议

作者： Dan Zhang Xin Chen Zhe Xiao School of Automation China University of Geosciences

Recent advancements in music generation research have significantly progressed the ***,a prevalent issue among current models is their tendency to overlook music's intrinsic structure,leading to compositions that lack coherence and thematic *** paper proposes a novel approach to structured music generation that addresses these challenges by considering music structure as styles of different *** approach enhances the deep structural aspects of generative music by deriving embedding vectors from pre-trained contrastive models and clustering them into discrete structured tokens for generative ***,this study introduces a self-similarity-based evaluation method to assess the structural features of the generated *** results indicate that the Structured music Transformer(SMT)significantly outperforms contemporary models in producing compositions that are stylistically coherent and structurally robust,as demonstrated across two diverse datasets.

关键词： music generation computer music neural networks deep learning machine learning

来源： cnki会议评论

在线全文

cnki会议

学校读者我要写书评

暂无评论

欢迎您,

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

请选择保存的检索档案：

请选择收藏分类：

通借通还

欢迎您,

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

在线全文

在线全文

在线全文

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：