Speech Coding for Universal Voice Communications

通用语音通信的语音编码

• 批准号: 0728646
• 负责人: Jerry Gibson
• 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: 2007
• 资助国家: 美国
• 起止时间: 2007-10-01 至 2011-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0728646&HistoricalAwards=false
• 关键词: Speech; Coding; Universal; Voice; Communications

Voice is the preferred mode of human communication. Our mostly homogeneous network for voice communications, the Public Switched Telephone Network, is quickly being replaced with a heterogeneous collection of wired and wireless links, including the wired Internet for voice over IP, digital cellular telephone systems, and voice over wireless access points. These links/networks are not jointly designed or standardized, and use different speech coders, so when they are interconnected, there is a significant loss of voice quality. Additionally, we are not well-positioned to take advantage of evolving networks, such as mesh and ad hoc networks, for voice communications. This research develops new speech coders that produce high quality, highly intelligible speech over a wide range of bit rates, with a full range of functionalities, and which are suitable for voice over IP, digital cellular, voice over wireless access points, and woice over wireless ad hoc/mesh networks. The resulting speech coders are especially important for the wireless networks deployed in emergency response situations.By combining phonetic mode detection and rate distortion theory motivated structures with backward adaptive tree codes, this research derives and develops new speech coders that are SNR and bandwidth scalable, have multiple descriptions functionality, tandem well with other codecs, and have excellent packet loss concealment. The resulting speech coders are important for ad hoc and mesh networks deployed in emergency response situations, where multicast transmissions are prevalent, SNR scalability is important to allow selective pruning of traffic, and multiple descriptions functionality is critical to take advantage of path diversity and provide enhanced reliability. This research establishes new fundamental limits on speech coder performance by combining multimodal speech models and conditional rate distortion theory.

语音是人类首选的交流方式。我们主要用于语音通信的同构网络公共交换电话网络正在迅速被各种有线和无线链路所取代，包括用于IP语音、数字蜂窝电话系统和无线接入点的有线互联网。这些链路/网络不是联合设计或标准化的，并且使用不同的语音编码器，因此当它们互连时，语音质量会有很大损失。此外，我们还不能很好地利用不断发展的网络，如网状网络和自组织网络，进行语音通信。这项研究开发了新的语音编码器，它可以在广泛的比特率下产生高质量、高清晰度的语音，具有全面的功能，并且适用于IP语音、数字蜂窝、无线接入点语音和无线自组织/网状网络。通过将语音模式检测和率失真理论激励结构与后向自适应树码相结合，推导并开发了具有信噪比和带宽可伸缩性、具有多描述功能、与其他编解码器很好地协同工作、具有良好的分组丢失隐蔽性的新的语音编码器。所得到的语音编码器对于在紧急响应情况下部署的自组织和网状网络是重要的，其中多播传输很普遍，SNR可伸缩性对于允许选择性地修剪流量是重要的，并且多描述功能对于利用路径分集和提供增强的可靠性是关键的。本研究结合多模式语音模型和条件率失真理论，为语音编码器的性能设定了新的基本限制。