I-Corps: Automatic Music Generation Using Artificial Intelligence and Music Theory

I-Corps：使用人工智能和音乐理论自动生成音乐

• 批准号: 1916649
• 负责人: Lu Lu
• 金额: $ 5万
• 依托单位: New Jersey Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-03-15 至 2020-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1916649&HistoricalAwards=false
• 关键词: Corps; Automatic; Music; Generation; Using

The broader impact/commercial potential of this I-Corps project is to revolutionize the music industry and related sectors such as game development and video production which significantly involve music. With the proposed music generation technology, copyright issues can be avoided since the music generated is completely original. Furthermore, compared to traditional composing methods which take at least an hour for the user or composer to produce a one-minute piece of music, the proposed technology spends only less than a minute to generate the music of the same length. These advantages will allow small game developers and self-media producers to generate original music that fit to their needs in a very short amount of time with minimum cost, which significantly benefits the game and self-media industries.This I-Corps project features the technology of automatic music generation from user's humming based on AI and music theory. Without any professional knowledge of music, a user can simply start by humming a short melody. Combining the AI algorithm with music theory, the application completes other necessary musical components (such as chord progression, beats and tempo) and expands the short input melody into a full piece of music for which the user can change genre and do post-editing. The technical differentiators of the proposed technology are threefold. Firstly, a pitch detection algorithm is developed to recognize the user's humming tune and turn it into musical notes, which are then optimized to conform to music theory and logic. Secondly, a novel algorithm combining Recurrent Neural Network and music theory is developed to generate a full piece of music, including the main melody, chord progression, motive and accompaniment, based on the user's short input melody. Thirdly, the post editing stage allows the user to modify the notes and genre according to the generated chord progression.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.

这个i-Corps项目的更广泛的影响/商业潜力是彻底改变音乐行业和相关部门，如游戏开发和视频制作，这些部门与音乐密切相关。使用建议的音乐生成技术，可以避免版权问题，因为生成的音乐完全是原创的。此外，与传统的作曲方法相比，用户或作曲家至少需要一个小时才能制作一段一分钟的音乐，而所提出的技术只需不到一分钟就可以生成相同长度的音乐。这些优势将允许小游戏开发商和自媒体制作人在极短的时间内以最低的成本制作出符合他们需求的原创音乐，这将使游戏和自媒体行业显著受益。这个i-Corps项目的特点是基于人工智能和音乐理论的用户哼唱自动生成音乐的技术。在没有任何音乐专业知识的情况下，用户可以简单地从哼唱一小段旋律开始。将人工智能算法与音乐理论相结合，该应用程序完成了其他必要的音乐组成部分(如和弦级数、节拍和节奏)，并将简短的输入旋律扩展为完整的音乐片段，用户可以对其进行流派转换和后期编辑。拟议技术的技术差异有三个方面。首先，开发了一种基音检测算法来识别用户的哼唱曲调，并将其转换为音符，然后对音符进行优化，以符合音乐理论和逻辑。其次，将递归神经网络和音乐理论相结合，提出了一种新的算法，能够根据用户输入的短旋律生成完整的乐曲，包括主旋律、和弦行进、动机和伴奏。第三，后期编辑阶段允许用户根据生成的和弦进度修改音符和流派。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。