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REU Site: Computational Methods for Understanding Music, Media, and Minds

REU Site: Computational Methods for Understanding Music, Media, and Minds
REU 网站:理解音乐、媒体和思想的计算方法
批准号:
1950460
负责人:
Ajay Anand
金额:
$40.5万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2020
资助国家:
美国
项目状态:
已结题
起止时间:
2020-03-01 至 2024-02-29

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中文摘要
翻译
计算机如何学习阅读古代手稿中隐藏的文字?如何训练计算机将音乐音频转录成乐谱或创作一首新歌?计算机系统能教会一个人更好地使用韵律--演讲的音乐模式--成为一个更有效的公共演讲者吗?这些是学生们将在罗切斯特大学本科生研究经验(REU)网站上调查的一些问题。学生将探索一个令人兴奋的跨学科研究领域,结合计算机科学,电气工程,认知科学和音乐。每个学生将由两名或两名以上的教师从工程,科学,艺术和音乐大学的学校指导。REU网站的其他活动包括职业发展研讨会;奖学金社区座谈会;研究生院准备;机器学习的Python编程;以及以音乐为重点的活动。该REU的目标是增加多样性,拓宽从事计算机科学研究的学生的视野。音乐,数字媒体和认知科学的主题将吸引许多来自计算机科学领域代表性不足的学生。该网站欢迎来自那些将计算方法,艺术和人文学科相结合的跨学科研究机会可能有限的机构的学生。已经主修计算机科学的学生会发现,该领域的研究不仅限于传统的工程应用,而且可以解决艺术,文化和人类心理学的问题。具有将计算机科学与人文研究相结合的经验的学生已经在工业界和学术界有很大的需求,并将有助于定义在21世纪世纪成为计算机科学家意味着什么。在这个REU的学生将从事跨学科的研究,结合机器学习,计算机试听,音乐理论和认知科学。这些学科通过使用一组共同的形式表示和计算方法而统一起来;特别是概率模型和机器学习。在研究活动中,REU学生将研究各种主题。其中包括:创建人机协作音乐制作系统;开发脑电图(EEG)分析方法来解码音乐思维;使用机器学习和多光谱成像来阅读古代手稿中的隐藏文本;研究韵律如何使一个人成为令人信服的公共演讲者;开发大数据技术来分析视听场景;以及探索人类和计算机自然语言处理之间的联系。该计划通过大学最近成立的音频和音乐工程计划以及与伊士曼音乐学院的合作关系得到加强。虽然REU的主要目标是鼓励学生进入STEM研究生课程,但许多项目可以预期会导致新颖和可持续的研究。该奖项反映了NSF的法定使命,并通过使用基金会的智力价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
How can a computer learn to read hidden text in ancient manuscripts? How can a computer be trained to transcribe music audio into music notation or compose a new song? Can a computer system teach a person to better use prosody — the musical pattern of speech – to become a more effective public speaker? These are some of the questions that students will investigate in this Research Experience for Undergraduates (REU) site at the University of Rochester. Students will explore an exciting, interdisciplinary research area that combines computer science, electrical engineering, cognitive science, and music. Each student will be mentored by two or more faculty members from the University's schools of engineering, sciences, arts, and music. Other activities of the REU site include workshops on career development; scholarship community colloquiums; graduate school preparation; Python programming for machine learning; and music-focused activities. The goals of this REU are to increase the diversity and broaden the horizons of students engaged in computer science research. The themes of music, digital media, and cognitive science will attract many students from groups under-represented in computer science. The site welcomes students from institutions where opportunities for interdisciplinary research combining computational methods, arts and humanities may be limited. Students who are already majoring in computer science will discover that the research in the field is not limited to traditional engineering applications, but can address questions of art, culture, and human psychology. Students with experience in combining computer science with humanistic research are already in great demand in industry and academia and will help define what it means to be a computer scientist in the 21st century. Students in this REU will engage in interdisciplinary research that combines machine learning, computer audition, music theory, and cognitive science. These disciplines are united by their use of a common set of formal representations and computational methods; in particular, probabilistic models and machine learning. In the research activities, REU students will work on a variety of topics. These include: creating human-computer collaborative music making systems; developing electroencephalogram (EEG) analysis methods to decode musical minds; using machine learning and multispectral imaging to read hidden text in ancient manuscripts; studying how prosody makes a person a convincing public speaker; developing big data techniques to analyze audio-visual scenes; and, exploring connections between human and computer natural language processing. The program is strengthened by the University's recently-founded audio and music engineering program, and the partnership with the Eastman School of Music. Although the major objective of the REU is to encourage students to enter STEM graduate programs, many of the projects can be expected to lead to novel and publishable research.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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REU Site: Computational Methods for Understanding Music, Media, and Minds
  • 批准号:
    1659250
  • 项目类别:
    Standard Grant
  • 资助金额:
    $32.4万
  • 财政年份:
    2017
  • 负责人:
    Ajay Anand
  • 依托单位:
国内基金
海外基金
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新型WDR5蛋白Win site抑制剂的合理设计、合成及其抗肿瘤活性研究
  • 批准号:
    82103981
  • 项目类别:
    青年科学基金项目(C类)
  • 资助金额:
    30.0万元
  • 批准年份:
    2021
  • 负责人:
    陈维琳
  • 依托单位:
基于重要农地保护LESA(Land Evaluation and Site Assessment)体系思想的高标准基本农田建设研究
  • 批准号:
    41340011
  • 项目类别:
    专项基金项目
  • 资助金额:
    20.0万元
  • 批准年份:
    2013
  • 负责人:
    钱凤魁
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