伽罗瓦域上的线性计算机音乐序列

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摘要翻译：
它显示了二进制序列如何能够与单声道片段的自动合成相关联。我们从有限场结构中研究电子音乐的合成。输入处的信息可以是随机的，也可以是来自黑白、灰度或彩色图片的信息。新的电子作曲和乐谱提供，包括从著名的Lenna图片的新作品：电子音乐的乐谱<<在Lenna的眼睛之间，C大调>>相应的乐谱延伸给出。提出了一些特殊的结构，包括时钟算法(MOD12)、GF(7)、GF(8)、GF(13)和GF(17)。此外，多级分组码也被用于电子音乐创作的一种新方法，产生了作为电子作曲家的特殊风格。作为一个例子，最近引入的Pascal多级分组码被处理以在GF(13)上生成新风格的电子音乐。
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英文标题：
《Linear Computer-Music through Sequences over Galois Fields》
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作者：
H.M. de Oliveira and R.C. de Oliveira
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最新提交年份：
2017
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分类信息：

一级分类：Computer Science        计算机科学
二级分类：Sound        声音
分类描述：Covers all aspects of computing with sound, and sound as an information channel. Includes models of sound, analysis and synthesis, audio user interfaces, sonification of data, computer music, and sound signal processing. Includes ACM Subject Class H.5.5, and intersects with H.1.2, H.5.1, H.5.2, I.2.7, I.5.4, I.6.3, J.5, K.4.2.
涵盖了声音计算的各个方面，以及声音作为一种信息通道。包括声音模型、分析和合成、音频用户界面、数据的可听化、计算机音乐和声音信号处理。包括ACM学科类H.5.5，并与H.1.2、H.5.1、H.5.2、I.2.7、I.5.4、I.6.3、J.5、K.4.2交叉。
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一级分类：Electrical Engineering and Systems Science        电气工程与系统科学
二级分类：Audio and Speech Processing        音频和语音处理
分类描述：Theory and methods for processing signals representing audio, speech, and language, and their applications. This includes analysis, synthesis, enhancement, transformation, classification and interpretation of such signals as well as the design, development, and evaluation of associated signal processing systems. Machine learning and pattern analysis applied to any of the above areas is also welcome.  Specific topics of interest include: auditory modeling and hearing aids; acoustic beamforming and source localization; classification of acoustic scenes; speaker separation; active noise control and echo cancellation; enhancement; de-reverberation; bioacoustics; music signals analysis, synthesis and modification; music information retrieval;  audio for multimedia and joint audio-video processing; spoken and written language modeling, segmentation, tagging, parsing, understanding, and translation; text mining; speech production, perception, and psychoacoustics; speech analysis, synthesis, and perceptual modeling and coding; robust speech recognition; speaker recognition and characterization; deep learning, online learning, and graphical models applied to speech, audio, and language signals; and implementation aspects ranging from system architecture to fast algorithms.
处理代表音频、语音和语言的信号的理论和方法及其应用。这包括分析、合成、增强、转换、分类和解释这些信号，以及相关信号处理系统的设计、开发和评估。机器学习和模式分析应用于上述任何领域也是受欢迎的。感兴趣的具体主题包括：听觉建模和助听器；声波束形成与声源定位；声场景分类；说话人分离；有源噪声控制和回声消除；增强；去混响；生物声学；音乐信号的分析、合成与修饰；音乐信息检索；多媒体音频和联合音视频处理；口语和书面语建模、切分、标注、句法分析、理解和翻译；文本挖掘；言语产生、感知和心理声学；语音分析、合成、感知建模和编码；鲁棒语音识别；说话人识别与特征描述；应用于语音、音频和语言信号的深度学习、在线学习和图形模型；以及从系统架构到快速算法的实现方面。
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英文摘要：
  It is shown how binary sequences can be associated with automatic composition of monophonic pieces. We are concerned with the composition of e-music from finite field structures. The information at the input may be either random or information from a black-and-white, grayscale or color picture. New e-compositions and music score are made available, including a new piece from the famous Lenna picture: the score of the e-music <<Between Lenna's eyes in C major.>> The corresponding stretch of music score are presented. Some particular structures, including clock arithmetic (mod 12), GF(7), GF(8), GF(13) and GF(17) are addressed. Further, multilevel block-codes are also used in a new approach of e-music composition, engendering a particular style as an e-composer. As an example, Pascal multilevel block codes recently introduced are handled to generate a new style of electronic music over GF(13).
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PDF链接：
https://arxiv.org/pdf/1709.06663

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关键词：计算机 Segmentation Applications cancellation Modification new 提供 计算机音乐 能够 codes