  News podcasts are a popular medium to stay informed and dive deep into news
topics. Today, most podcasts are handcrafted by professionals. In this work, we
advance the state-of-the-art in automatically generated podcasts, making use of
recent advances in natural language processing and text-to-speech technology.
We present NewsPod, an automatically generated, interactive news podcast. The
podcast is divided into segments, each centered on a news event, with each
segment structured as a Question and Answer conversation, whose goal is to
engage the listener. A key aspect of the design is the use of distinct voices
for each role (questioner, responder), to better simulate a conversation.
Another novel aspect of NewsPod allows listeners to interact with the podcast
by asking their own questions and receiving automatically generated answers. We
validate the soundness of this system design through two usability studies,
focused on evaluating the narrative style and interactions with the podcast,
respectively. We find that NewsPod is preferred over a baseline by
participants, with 80% claiming they would use the system in the future.
