I-Corps: Music in the Numbers

I-Corps：数字中的音乐

• 批准号: 1834992
• 负责人: Glenn McClure
• 金额: $ 5万
• 依托单位: SUNY College at Geneseo
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-07-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1834992&HistoricalAwards=false
• 关键词: Corps; Music; Numbers

The broader impact/commercial potential of this I-Corps project is driven by novel software within an automated digital engine, performing sonification that translates numerical sequences of archived and real-time data streams into sound. The software has applications in multiple industries that will benefit from ongoing interpretation of big data using non-speech audio to represent data. The audio feed will be paralleled with visual representation, allowing the user instant access to expanded information. The human ear is superior to the eye for processing certain kinds of information, especially information that changes over time. As an alternative or complement to visual analysis, audio perception can process data in temporal, spatial, amplitude, and frequency resolution. Shifting ongoing trend analysis and anomaly detection to audio will reduce visual data overload. Audio interpretation allows users to multi-task while listening to an audio stream of archived or real-time data. Sonification offers audio icons to visually impaired users and provides an alternative learning mode for diverse learners. It is an efficacious tool for trend analysis and anomaly detection for diverse industries, such as health, medicine, finance, defense, aviation, manufacturing, security, including homeland and home security fields, and other endeavors requiring analysis of big data. This I-Corps project was born from an Antarctic Artists and Writers Program award from NSF's Office of Polar Programs. It represents the fusion of artistic and scientific expertise toward the development of a new data analysis tool. This project combines both automated sonification of data with customized interpretation that responds to a variety of aesthetic and ethnic sensibilities. Audio backgrounds can be customized based upon diverse music styles, including but not limited to, jazz, calypso, classical, rock. Elements of customization happen outside of the algorithm. The algorithm produces a melody of notes coming from a data feed. User customizations provide an appropriate customized rhythm track as well as a chord progression or program that would harmonize with the melody produced. Information overload lowers employee productivity, according to Harvard Business Review (Hemp 2009). Given this overload and data analysis needs in many markets, this product could be launched in diverse markets, including financial trading, intensive care medicine, factory process control, air traffic control, security monitoring, soldier awareness, and markets with unmanageable flows of critical real time data with resulting data comprehension and response time errors.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项目更广泛的影响/商业潜力是由自动化数字引擎中的新型软件驱动的，该软件执行将存档和实时数据流的数字序列转换为声音的声音处理。该软件在多个行业都有应用，这些行业将受益于使用非语音音频来表示数据的大数据的持续解释。音频馈入将以视觉表示形式显示，允许用户即时访问扩展的信息。人耳在处理某些信息方面比眼睛优越上级，尤其是那些随时间变化的信息。作为视觉分析的替代或补充，听觉感知可以在时间，空间，幅度和频率分辨率上处理数据。将正在进行的趋势分析和异常检测转移到音频将减少视觉数据过载。音频解释允许用户在收听存档或实时数据的音频流时进行多任务处理。Sonification为视障用户提供音频图标，并为不同的学习者提供另一种学习模式。它是一个有效的工具，用于不同行业的趋势分析和异常检测，例如健康，医药，金融，国防，航空，制造业，安全，包括国土和家庭安全领域，以及其他需要分析大数据的工作。这个I-Corps项目诞生于NSF极地项目办公室的南极艺术家和作家项目奖。它代表了艺术和科学专业知识的融合，以开发新的数据分析工具。该项目将数据的自动化发音与定制的解释相结合，以响应各种美学和种族情感。音频背景可以基于不同的音乐风格来定制，包括但不限于爵士乐、卡里普索、古典、摇滚。定制元素发生在算法之外。该算法产生来自数据馈送的音符的旋律。用户定制提供适当的定制节奏轨道以及和弦进行或将与所产生的旋律协调的程序。根据哈佛商业评论（Hemp 2009），信息过载会降低员工的生产力。鉴于许多市场的这种过载和数据分析需求，该产品可以在不同的市场推出，包括金融交易，重症监护医学，工厂过程控制，空中交通管制，安全监控，士兵意识，和市场，关键的真实的时间数据流无法管理，导致数据理解和响应时间错误。该奖项反映了NSF的法定使命，并被认为值得支持通过使用基金会的知识价值和更广泛的影响审查标准进行评估。