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中文摘要：
在分析目前主要预取算法优劣的基础上，根据VoiceXML语音平台与基于HTML的www之间的区别，提出了在VoiceXML语音平台中应该预取其引用的语音资源．在采用基于热点预取技术的同时，提出了一种自适应的多用户共享的Markov模型，可以统一预测所有在线用户下一步所需的资源及其访问概率，有助于提高预测的准确率．仿真研究表明，与单用户Markov预测模型相比较，这种多用户共享的Markov预测模型能在相同带宽消耗下得到更好的命中率，减少用户请求的访问延迟，提高响应速度。
英文摘要：
By analyzing the present dominating prefetch algorithms＇ advantages and disadvantages, according to the difference between VoiceXML-based voice platform and HTML-based world wide web, it is proposed that the cited voice resource should be prefetched in VoiceXML-based voice platform. At the same time of adopting the hot-spot-based prefetch technology, an adaptive multi-user shared Markov prediction model is presented, which can predict the forthcoming required resource of all the online users and its probability to improve the accuracy of the prediction. The simulation research showed that this multi-user shared Markov prediction model could get a higher hit ratio, reduce delay of a user＇s request and improve response speed comparing with the single-user Markov prediction model with the same consumed bandwidth.
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