When people listen to stories, the words are colored with emotions conveyed through prosodic features beyond the text alone. Visual font design provides an opportunity to enhance the empathic quality of a story compared to plain text. In this paper, we present the design, implementation, and evaluation of Affective Typography (AffType), an AI-driven system that extracts prosodic information and sentiment from speech and maps these properties to typographic styles. We conduct a crowdsourced study (N=140) to assess how different font design elements impact readers' empathy with personal stories. While our empathy survey results were not statistically significant, we found that participants had a preference for color to express emotion and saw an increase in average empathy for stories with color-based text alterations. In addition, we offer design insights as to what display features best convey emotional qualities of personal stories for future applications that use affective fonts to create more expressive digital text.