SBIR Phase I: Realtime Automatic Accompaniment for Music Games

SBIR第一期：音乐游戏实时自动伴奏

• 批准号: 1113681
• 负责人: Prerna Gupta
• 金额: $ 15万
• 依托单位: Khush Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-07-01 至 2012-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1113681&HistoricalAwards=false
• 关键词: SBIR; Phase; Realtime; Automatic; Accompaniment

This Small Business Innovation Research Phase I project investigates the technical and commercial feasibility of a realtime automatic accompaniment technology. The proposed innovation would allow a computer to improvise in realtime with a human musician. The intellectual merit of this proposal is in researching a novel computational framework for modeling musical interaction. Realtime improvisation is one of the most demanding cognitive tasks that humans undertake. This proposal seeks to model the sequential structure of melodies and realtime interaction between two improvising musicians. Although music is a creative act, often full of small surprises, it nevertheless is highly patterned. The prediction methods described in this proposal attempt to uncover this structure through context-dependent models. Realtime musical interaction in the context of tonal music is a relatively new area of research, and the cognitive and musical strategies by which musicians coordinate are complex. The research plan will explore whether this intuitive negotiation can be modeled using game theory, with musically appropriate ideas of payoff. The researchers will evaluate both methods using cross-entropy, an objective measure of how well the predictive distribution matches the actual sequence data. The objective of this proposal is to develop a RAA technology that facilitates technology-based music creation among people that are not musically trained and, in so doing, leads to a new class of self-expression products that represent a multi-billion dollar commercial opportunity. Further, the approach may have clinical applications in the areas of speech therapy for stroke patients suffering speech loss and children with developmental disorders.

这个小企业创新研究第一阶段项目调查了实时自动伴奏技术的技术和商业可行性。这项提议的创新将允许计算机与人类音乐家实时即兴创作。该建议的智力价值在于研究了一种新的音乐交互建模计算框架。实时即兴创作是人类承担的最苛刻的认知任务之一。这个提议试图模拟旋律的顺序结构和两个即兴音乐家之间的实时互动。虽然音乐是一种创造性的行为，经常充满小惊喜，但它仍然是高度模式化的。本建议中描述的预测方法试图通过上下文相关模型揭示这种结构。调性音乐背景下的实时音乐互动是一个相对较新的研究领域，音乐家协调的认知和音乐策略是复杂的。研究计划将探索这种直觉谈判是否可以用博弈论来建模，并具有音乐上合适的回报理念。研究人员将使用交叉熵来评估这两种方法，交叉熵是一种衡量预测分布与实际序列数据匹配程度的客观指标。这项提案的目标是开发一种RAA技术，促进那些没有受过音乐训练的人进行基于技术的音乐创作，并由此产生一种新的自我表达产品，这代表着数十亿美元的商业机会。此外，该方法可能在中风失语患者和发育障碍儿童的语言治疗领域具有临床应用价值。