In our information-driven web-based society, we are all gradually falling "victims" to information overload .However, while sighted people are finding ways to sift through information faster, Internet users who are blind are experiencing an even greater information overload. These people access computers and Internet using screen-reader software, which reads the information on a computer screen sequentially using computer-generated speech. While sighted people can learn how to quickly glance over the headlines and news articles online to get the gist of information, people who are blind have to use keyboard shortcuts to listen through the content narrated by a serial audio interface. This interface does not give them an opportunity to know what content to skip and what to listen to. So, they either listen to all of the content or listen to the first part of each sentence or paragraph before they skip to the next one. In this paper, we propose an automated approach to facilitate non-visual skimming of web pages. We describe the underlying algorithm, outline a non-visual skimming interface, and report on the results of automated experiments, as well as on our user study with 23 screen-reader users. The results of the experiments suggest that we have been moderately successful in designing a viable algorithm for automatic summarization that could be used for non-visual skimming. In our user studies, we confirmed that people who are blind could read and search through online articles faster and were able to understand and remember most of what they have read with our skimming system. Finally, all 23 participants expressed genuine interest in using non-visual skimming in the future.