CAREER: Agile Speech and Audio Coding and Transmission over Heterogeneous Networks

职业：异构网络上的敏捷语音和音频编码和传输

• 批准号: 0347229
• 负责人: Manohar Narayanamurthi
• 金额: $ 40万
• 依托单位: University of Miami
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-02-15 至 2011-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0347229&HistoricalAwards=false
• 关键词: CAREER; Agile; Speech; Audio; Coding

During emergencies, communication networks are characterized by their high degree of variability in terms of link failure and packet loss. However, current Voice over Internet Protocol (VoIP) methods deliver dissatisfactory performance during emergencies, lacking both the agility to adapt to demanding network conditions, and a systematic framework for measuring voice Quality-of-Service (QoS). The goal of this research is to provide a VoIP framework and methods suitable for demanding network situations. By furnishing methods for achieving voice communication during emergencies or other demanding situations such as distance-learning, this research will provide an immeasurable benefit to society. The highly dynamic nature of channels and networks necessitates cross-layer design approaches in which parameters across all layers of a protocol stack are optimized to efficiently maximize application QoS. To integrate VoIP into a cross-layer design framework, this research offers a new paradigm for speech and audio coding together with several novel error control and transmission methods. In particular, this research provides a functional layering approach to speech and audio coding, breaking up the operation of the coder into three ascending, hierarchical layers: the Waveform Layer, the Statistical Layer, and the Expected Distortion Layer. At the Waveform Layer, a signal is decomposed into perceptually relevant objects whose evolution through time is tracked at the Statistical Layer. Quantization is performed at the Statistical Layer with direction from the Expected Distortion Layer. The Expected Distortion Layer calculates voice QoS for various coder, error-control, and transmission parameter settings, allowing cross-layer optimization based adaptive resource allocation. This paradigm engenders a unique unified model for coding and packet loss concealment, enabling perceptually-adaptive packet protection, transmission, and traffic engineering over time-varying heterogeneous wired and wireless networks.

在紧急情况下，通信网络的特征是它们在链接故障和数据包丢失方面的高度可变性。但是，当前关于Internet协议（VOIP）方法的语音在紧急情况下提供了不满意的性能，缺乏适应苛刻网络条件的敏捷性，也缺乏用于测量语音服务质量（QoS）的系统框架。 这项研究的目的是提供适合要求网络情况的VoIP框架和方法。通过提供在紧急情况或其他苛刻情况（例如远程学习）中实现语音交流的方法，这项研究将为社会带来无可估量的好处。 通道和网络的高度动态性质需要跨层设计方法，在该方法中，对协议堆栈的所有层的参数进行了优化，以有效地最大化应用程序QoS。为了将VoIP集成到跨层设计框架中，这项研究提供了一种新的语音和音频编码范式以及几种新颖的错误控制和传输方法。特别是，这项研究为语音和音频编码提供了一种功能分层方法，将编码器的操作分为三个上升的分层层：波形层，统计层和预期的失真层。在波形层，一个信号分解为感知相关的对象，其在统计层处跟踪其通过时间的演变。量化是从预期失真层的方向上进行统计层进行的。预期失真层计算各种编码器，错误控制和传输参数设置的语音QoS，从而允许基于跨层优化的自适应资源分配。该范式为编码和数据包丢失隐藏而产生了独特的统一模型，从而可以通过感知自适应的数据包保护，传输和交通工程，而随着时间变化的异质有线和无线网络。