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.

声音是人类交流的首选模式。我们主要用于语音通信的均质网络，即公共交换电话网络，迅速被有线和无线链接的异质集合所取代，包括用于IP上语音的有线互联网，数字蜂窝电话系统以及无线访问点上的语音。这些链接/网络不是共同设计或标准化的，并且使用不同的语音编码器，因此，当它们相互联系时，语音质量会大大损失。此外，我们没有很好地利用不断发展的网络（例如网格和临时网络）进行语音通信。这项研究开发了新的语音编码器，这些编码者在多种比特率上产生高质量，高度可理解的语音，具有全范围的功能，并且适用于IP上的语音，数字蜂窝，无线访问点上的语音，以及无线临时/网格网络上的问题。 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.由此产生的语音编码器对于在紧急响应情况下部署的临时和网格网络很重要，在此情况下，多播式传输很普遍，SNR可伸缩性对于允许对流量的选择性修剪很重要，并且多个描述功能对于利用路径多样性并提供增强的可靠性至关重要。这项研究通过结合多模式语音模型和条件速率失真理论来建立对语音编码者绩效的新基本限制。