CIF: Small: A Resource-Scalable Unifying Framework for Aural Signal Coding

CIF：小型：用于音频信号编码的资源可扩展统一框架

• 批准号: 0917230
• 负责人: Kenneth Rose
• 金额: --
• 依托单位: University of California-Santa Barbara
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-07-01 至 2013-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0917230&HistoricalAwards=false
• 关键词: CIF; Small; Resource; Scalable; Unifying

"This award is funded under the American Recovery and Reinvestment Act of 2009(Public Law 111-5)."A Resource-Scalable Unifying Framework for Aural Signal CodingThe objective of this project is to achieve a comprehensive, unifying framework and corresponding universal methodologies for the coding of aural signals. The challenges are due to the combination of elusive perceptual criteria, complex signal structures, and great diversity in signal type, operational setting, complexity and delay requirements. Historical efforts were tailored to narrowly defined signal types and scenarios, such as linear prediction for low rate speech communication versus transform-based music coding for storage and streaming. However, there is a growing realization of their insufficiency to handle the heterogeneous aural signals and network settings encountered in many real-world applications, as evidenced in particular by recent major initiatives of the multimedia and networking industries demanding joint speech-audio coding standardization. The research formalizes the tradeoffs that underly universal aural signal coding, and develops a unifying framework and methodologies to enable efficient optimization of resource-scalable coding under heterogeneous signal and network setting scenarios. The main thrusts of the project are: i) Development of a unifying resource-scalable framework coupled with effective perceptual distortion criteria, which covers the continuous gamut of aural signal types and networking scenarios, and is scalable in bit rate, encoding/decoding complexity and delay, etc.; ii) Theoretical analysis of rate-(perceptual) distortion performance limits within such unified compression paradigms; iii) A new class of universal methodologies and effective optimization algorithms for efficient coder design and various resource allocation within this unifying framework.

“这个奖项是根据2009年美国复苏和再投资法案(公法111-5)资助的。”一个资源可扩展的音频信号编码统一框架这个项目的目标是实现一个全面的、统一的框架和相应的通用音频信号编码方法。这些挑战是由于难以捉摸的感知标准、复杂的信号结构以及信号类型、操作环境、复杂性和延迟要求的巨大多样性。历史上的努力是为狭义定义的信号类型和场景量身定做的，例如用于低速率语音通信的线性预测与用于存储和流媒体的基于变换的音乐编码。然而，越来越多的人意识到它们不足以处理在许多真实世界应用中遇到的不同种类的音频信号和网络设置，特别是多媒体和网络行业要求联合语音-音频编码标准化的最近的主要倡议证明了这一点。这项研究正式确定了通用音频信号编码的权衡，并开发了一个统一的框架和方法，以实现在不同信号和网络环境场景下资源可伸缩编码的高效优化。该项目的主要任务是：i)开发一个统一的资源可扩展框架，结合有效的感知失真标准，它涵盖了音频信号类型和网络场景的连续色域，并且在比特率、编码/解码复杂度和延迟等方面是可扩展的；ii)在这种统一的压缩范例中对率(感知)失真性能限制进行理论分析；iii)在这个统一的框架内，为高效的编码器设计和各种资源分配提供一类新的通用方法和有效的优化算法。