Robust and quality-assured audio-visual communication

强大且有质量保证的视听通信

• 批准号: 121761-2006
• 负责人: Chan, WaiYip(Geoffrey)
• 金额: $ 1.68万
• 依托单位: Queen's University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2008
• 资助国家: 加拿大
• 起止时间: 2008-01-01 至 2009-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=391230
• 关键词: Robust; quality; assured; audio; visual

Auditory perceptual modeling of distortions plays a vital role in enabling today's widespread utilization of compressed speech and audio. Every voice conversation over a cellular telephone or download of MP3 music entails the use of perceptual-model based measurement of distortions.  When a speech or audio signal is compressed into a digital format, a distortion model is used to determine where in the signal to "hide" distortions to make them least perceptible. We propose to research using a new generation of perceptual models to build more powerful tools for speech communication and audio distribution over emerging and future network configurations.   One goal is to build machine intelligence to enable computers to rate the quality of a speech signal in the same manner as a panel of human listeners.  This would enable communication network elements and electronic devices to better optimize resource usage in accordance with human-perceived speech quality. Another goal is to devise new digital formatting algorithms that would enable efficient and reliable distribution of audio to a very large number of clients. The format will be very flexible so that the user-perceived audio quality at each client is the best possible given the particular quality of the client's network connection.  One anticipated benefit is that high-fidelity audio net-casting can reach a much greater number of users.

失真的听觉感知建模对于当今压缩语音和音频的广泛使用发挥着至关重要的作用。通过蜂窝电话进行的每次语音对话或 MP3 音乐的下载都需要使用基于感知模型的失真测量。  当语音或音频信号被压缩为数字格式时，失真模型用于确定信号中的何处“隐藏”失真以使其最不易被察觉。我们建议研究使用新一代感知模型来构建更强大的工具，用于在新兴和未来的网络配置上进行语音通信和音频分发。   一个目标是建立机器智能，使计算机能够以与人类听众相同的方式评估语音信号的质量。  这将使通信网络元件和电子设备能够根据人类感知的语音质量更好地优化资源使用。另一个目标是设计新的数字格式化算法，使音频能够高效、可靠地分发给大量客户。该格式将非常灵活，以便在给定客户端网络连接的特定质量的情况下，每个客户端的用户感知音频质量是最好的。  预期的好处之一是高保真音频网络广播可以覆盖更多的用户。