AI-driven Sound Analysis

该项目将研究提出用于声音分析和合成的新的机器学习方法。这包括将不同的声源从混合录音中分离出来，以及重新灌录和合成新的剧本。根据计算学院对博士生的指导，学生将在前四个月主要专注于文献回顾，并在第四个月结束时生成第一份正式报告。这份报告应该是对所提出的研究主题的全面的文献回顾，并确定一些可能的研究方向。在第九个月结束时，学生将在第一年结束时提交一份符合转学目的的第一年报告。该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的未来计划。博士进展将从第二年开始每年审查一次。第一阶段的研究将集中在声音分析，特别是如何从母版/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一阶段的主要目标。为此将提出新的机器学习方法。第二阶段将专注于将声音提取方法扩展到不同的应用中。这类应用可能包括从现有录音中重新掌握声道，用提取的声音合成新的声道，为不同的应用程序动态生成声音，例如虚拟现实。这项研究正好符合EPSRC的研究领域：视觉、听觉和其他感官，横跨多个领域，包括人工智能技术和人机交互，以及音乐和声学技术。

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.