SBIR Phase II: An Interactive Music Analysis, Re-synthesis and Distribution Engine

这个小型企业创新研究第二阶段项目旨在扩展开发计算音乐系统的工作，该系统将自动分析和重新合成数字音乐，以将线性和被动的音乐聆听实践转化为互动，表达和创造性的音乐体验。在第一阶段的工作基础上，重点是分段和用户交互，该公司建议将工作扩展到以下领域：利用机器学习技术提取音乐片段的乐器内容;开发自动作曲技术，对注释的音乐片段进行排序，以创建有音乐意义的作品;开发用于表示音乐作品的可视化技术;利用我们的技术开发一套应用程序，并实现基于云的服务，支持与这些应用程序的无缝交互。 该项目的智力价值在于对音乐感知和分析，机器学习，自动作曲，用户交互和可视化领域的人类知识的基本贡献。该项目将推进音乐信息检索、音乐感知、机器学习、自动作曲、信号处理、可视化和云计算等领域的现有知识。这项研究将揭示更广泛的概念，如人类和人工的创造力和表达，以及利用人工音乐智能作为儿童，新手和专家的新型音乐创造力的推动者的可行性。该项目将通过为所有技能水平的用户创造引人入胜和有益的音乐体验，在公共领域产生广泛的影响。祖兹？的音乐智能引擎将允许即使是那些谁认为他们不是音乐倾向，成为从事表达和创造性的音乐体验。作为该项目的一部分，我们将继续与教育和音乐机构举办研讨会，让儿童和新手使用Zooz引擎进行互动和创作音乐。将举办高知名度的公共音乐会，将这项技术带到公众面前。从商业角度来看，该项目的广泛影响在于为当今音乐行业面临的重大问题提供了一种新颖的解决方案。该行业的音乐销量每年大幅下降，正在寻找新的方法，通过让粉丝参与音乐游戏、个性化工具和基于云的音乐互动来将其内容货币化。Zooz移动的将通过提供一个智能系统来满足这些需求，该系统将允许粉丝以新颖和富有表现力的方式在云端进行互动，个性化和分享他们最喜欢的音乐。

This Small Business Innovation Research Phase II project aims to extend work in developing computational music systems that will automatically analyze and re-synthesize digital music for the purpose of transforming a linear and passive music listening practice into an interactive, expressive and creative music experiences. Building on the work in phase I, which focused on segmentation and user interaction, the company propose to extend the work in the following areas: Utilizing machine-learning techniques to extract instrumental content of musical segments; Developing automatic compositional techniques that would sequence annotated musical segments to create musically meaningful compositions; Developing visualization techniques for representing musical compositions; Develop a set of applications utilizing our technology, and implement a Cloud based service that would support seamless interaction with these applications. The intellectual merit of the project lies in the fundamental contribution to human knowledge in the areas for music perception and analysis, machine learning, automatic composition, user interaction, and visualization. The project will advance current knowledge in areas such as music information retrieval, music perception, machine learning, automatic composition, signal processing, visualization and cloud computing. The proposed research would shed light on broader concepts such as human and artificial creativity and expression and the feasibility of utilizing artificial music intelligence as an enabler of novel forms of music creativity for children, novices and experts.The project will lead to broad impact in the public sphere by creating engaging and rewarding musical experience for users at all skill levels. Zooz?s music intelligence engine will allow even those who believe they are not musically inclined to become engaged in expressive and creative musical experiences. As part of the project, we will continue to conduct workshops with educational and musical institutions where children and novices will interact and create music using the Zooz engine. High visibility public concerts will be conducted to bring the technology to the public eye. From a business perspective, the broad impact of the project is in providing a novel solution to the significant problems faced by the music industry today. The industry, which has suffered from a significant annual drop in music sales, is looking for new ways to monetize their content by engaging fans with music games, personalization tools and cloud-based musical interaction. Zooz Mobile will address these needs by providing an intelligent system that will allow fans to interact, personalize and share their favorite music in the Cloud in novel and expressive manners.