AI-driven Sound Analysis

人工智能驱动的声音分析

• 批准号: 2436014
• 金额: --
• 依托单位: University of Leeds
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2020
• 资助国家: 英国
• 起止时间: 2020 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2436014
• 关键词: AI; driven; Sound; Analysis

The project will look into proposing new machine learning methods for sound analysis and synthesis. This includes separating different sound sources from mixed recordings, and remastering and synthesising new scenarios. In line with the School of Computing guidance for PhD students, the student will mainly focus on literature review in the first four months and produce the first formal report at the end of the fourth month. The report should be a comprehensive literature review on the proposed research topic and also identify a few possible research directions.At the end of the ninth month, the student will produce the first-year report which serves the purpose of the transfer viva by the end of the first year. The report will include the formal introduction and statement of the PhD topic, a comprehensive literature review, current work progresses and future plans for the remaining of the PhD.The PhD progress will be reviewed annually from the second year.The first stage of the research will focus on sound analysis, especially in how to isolate different sound sources from mastered/mixed audio files. Extracting different sounds from mixed audio files will be the main goal of this stage. New machine learning methods will be proposed for this purpose.The second stage will focus on extending the sound extraction methods into different applications. Such applications might include re-mastering the sound tracks from existing recordings, synthesising new tracks with extracted sounds, dynamic sound generation for different applications, e.g. Virtual Reality.The research fits squarely into EPSRC's research area 'Vision, hearing and other senses', spanning across multiple areas including Artificial Intelligence Technologies and Human-Computer Interaction, and Music and Acoustic Technology.

该项目将研究为声音分析和合成提出新的机器学习方法。这包括从混合录音中分离不同的声源，以及重新灌制和合成新的场景。根据计算机学院对博士生的指导，学生将在前四个月主要进行文献综述，并在第四个月结束时发表第一份正式报告。该报告应该是一个全面的文献综述提出的研究课题，并确定一些可能的研究方向。在第9个月结束时，学生将提交第一年报告，该报告将在第一年结束时用于转学。报告将包括博士课题的正式介绍和陈述，全面的文献综述，目前的工作进展和博士剩余部分的未来计划。从第二年开始，每年对博士生的学习进度进行评审。研究的第一阶段将集中在声音分析上，特别是如何从母带/混合音频文件中分离不同的声源。从混合音频文件中提取不同的声音将是这个阶段的主要目标。为此将提出新的机器学习方法。第二阶段的重点是将声音提取方法扩展到不同的应用领域。这些应用可能包括从现有录音中重新控制音轨，用提取的声音合成新的音轨，为不同的应用动态生成声音，例如虚拟现实。这项研究完全符合EPSRC的研究领域“视觉、听觉和其他感官”，跨越多个领域，包括人工智能技术和人机交互，以及音乐和声学技术。