STTR Phase I: Automated Music Theory Instruction for Secondary and Post-Secondary Education

STTR第一阶段项目为音乐教育市场开发自动化教学，用音乐分析算法取代人工，用数字多媒体文档取代纸质课程材料。尽管艺术教育对成绩有积极影响，但许多艺术项目正在被削减或资金不足；因此，这些学生成绩较差、无法完成大学学位的风险更高。学习音乐需要广泛的练习和个性化的指导，数百年来，私人课程一直在教授这一点。建议的解决方案为市场带来了一个独特的创新软件系统，它将使音乐理论教学的大部分内容自动化并得到加强。初步结果表明，这项技术可以改善学习，从而减少在较高年级进行补救的需要，并帮助美国学校在面临预算压力的情况下保持艺术教育的好处。许多研究表明，加强对艺术教育的重视可以激发智力，并创造更广泛的好处，如在STEM(科学、技术、工程和数学)和人际交往技能方面的便利。这是一个拥有数百万学生的市场，并扩展到更大的市场，例如世界各地的业余音乐家。该软件的关键创新在于其专有的音乐分析算法，使大量的音乐理论教学能够实现自动化，包括在调性音乐分析和作曲中对复杂的、第二级的和第二级的练习进行接近实时的校正、反馈和评分。通过使用该软件取代纸质教学材料，音乐学生可以根据需要练习作曲和分析，以掌握主题，并从数字教师那里获得即时反馈和指导。对于音乐教师来说，这项技术完全消除了给论文评分的需要，只需按一下按钮，他们现在每周几个小时的人力劳动就会减少到几秒钟。该软件实现了一个多媒体文档模型，集成了音乐理论教学中使用的所有常见媒体类型：音乐符号(带或不带自动分析)、MIDI(乐器数字接口)、文本编辑、图像、矢量图形、视频和音频回放。初步结果表明，这项技术改善了学习，从而减少了在较高年级进行补救的需要，并有助于在面临预算压力的情况下保持美国学校艺术教育的好处。

This STTR Phase I project develops automated instruction for the music education market, replacing human labor with music analysis algorithms, and paper course materials with digital multimedia documents. Despite the positive effects of art education on achievement, many arts programs are being cut or underfunded; as a result these students are at higher risk of poorer grades and not completing their college degrees. Learning music requires extensive practice and individualized guidance, as taught in private lessons for hundreds of years. The proposed solution brings a unique and innovative software system to the marketplace that will automate and reinforce substantial parts of music theory instruction. Early results indicate that this technology can improve learning thereby reducing the need for remediation at higher grade levels and helping maintain the benefits of arts education in US schools even in the face of budgetary pressures. Numerous studies have demonstrated that increased emphasis on education in the arts stimulates intellectual capacity and creates wider benefits such as facility in STEM (Science, Technology, Engineering, and Mathematics) and interpersonal skills. This is a market of millions of students with extensions into larger markets, such as amateur musicians throughout the world.The key innovation of the software lies in its proprietary music analysis algorithms that enable substantial amounts of music theory instruction to be automated, including close to real-time correction, feedback and grading of complex, secondary and post-secondary exercises in tonal music analysis and composition. By using the software in place of paper instruction materials, a music student can practice composition and analysis as much as needed to master topics, receiving instantaneous feedback and guidance from the digital teacher. For music instructors, the technology completely removes the need to grade papers, reducing what now takes them hours of human labor per week to seconds at the push of a button. The software implements a multimedia document model that integrates all the common types of media used in music theory pedagogy: music notation (with or without automatic analysis), MIDI (Musical Instrument Digital Interface), text editing, images, vector graphics, video and audio playback. Early results indicate that this technology improves learning, thereby reducing the need for remediation at higher grade levels and helping maintain the benefits of arts education in US schools even in the face of budgetary pressures.