SBIR Phase II: Sound-object Recognition for Real-time or Offline Systems

SBIR 第二阶段：实时或离线系统的声音对象识别

• 批准号: 1026435
• 负责人: Jason LeBoeuf
• 金额: $ 50万
• 依托单位: Imagine Research, Inc
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-08-15 至 2014-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1026435&HistoricalAwards=false
• 关键词: SBIR; Phase; II; Sound; object

This Small Business Innovation Research (SBIR) Phase II project includes research and development of audio recognition and analysis software for offline and real-time sound recognition. Musicians and audio engineers have access to terabytes of music loops and sound effects. However, musicians are limited to searching for sounds using text-only keyword searches. This is a mundane, inaccurate, and exhausting process that ignores the files' actual audio content. The proposed solution provides a unique "find-something-that-sounds-like-this" search engine. Media production software and hardware is too complex, tedious, and labor-intensive for both novice and advanced users. The proposed sound platform adds capability that was previously missing - recognizing an input sound and automatically choosing the best parameters for the user. This project uses a signal processing and machine learning platform to perform novel experiments for classifying audio streams in real-time, improving recognition accuracy, and retrieving sounds from large collections. Commercial-quality software development kits for offline and real-time sound recognition will be developed. This project integrates state-of-the-art machine learning, digital signal processing, and information retrieval techniques. If successful, the platform will be able to listen to an audio signal and understand what it is listening to - as human listeners can identify and classify sounds. This innovative technology will be licensed to audio and music technology software and hardware manufacturers. The platform is suited for long-term discoveries and innovation, with demonstrated commercial interest from biomedical signal processing, security/surveillance, and interactive gaming companies. In the first chosen market, (sound engineering) the platform will have direct cultural benefits for musicians, music hobbyists, and audio engineers. It will allow music creation and audio production to become a completely creative task - minimizing the tedious technical issues that hinder the creative process, and lowering the barriers to entry for novice musicians and creative professionals.

这个小型企业创新研究(SBIR)第二阶段项目包括研究和开发用于离线和实时声音识别的音频识别和分析软件。音乐家和音响工程师可以访问数TB的音乐循环和音效。然而，音乐人仅限于使用纯文本关键字搜索声音。这是一个平凡、不准确且令人精疲力竭的过程，它忽略了文件的实际音频内容。建议的解决方案提供了一个独特的“查找听起来像这样的东西”的搜索引擎。无论是新手还是高级用户，媒体制作软件和硬件都过于复杂、繁琐和劳动密集型。拟议的声音平台增加了以前缺少的功能-识别输入声音并自动为用户选择最佳参数。该项目使用一个信号处理和机器学习平台，为实时分类音频流、提高识别精度和从大量集合中检索声音进行新颖的实验。将开发用于离线和实时声音识别的商业质量软件开发工具包。该项目集成了最先进的机器学习、数字信号处理和信息检索技术。如果成功，该平台将能够收听音频信号，并理解它正在收听的内容--就像人类听众可以识别和分类声音一样。这项创新技术将授权给音频和音乐技术软件和硬件制造商。该平台适合长期发现和创新，生物医学信号处理、安全/监控和互动游戏公司表现出了商业兴趣。在第一选择的市场，(音响工程)平台将为音乐家、音乐爱好者和音频工程师带来直接的文化利益。它将使音乐创作和音频制作成为一项完全有创意的任务-将阻碍创作过程的繁琐技术问题降至最低，并降低新手音乐家和创意专业人士的准入门槛。