From my pen to your ears: automatic production of radio plays from unstructured story text

A radio play is a form of drama which exists in the acoustic domain and is usually consumed over broadcast radio. In this paper a method is proposed that, given a story in the form of unstructured text, produces a radio play that tells this story. First, information about characters, acting lines, and environments is retrieved from the text. The information extracted serves to generate a production script which can be used either by producers of radiodrama, or subsequently used to automatically generate the radio play as an audio file. The system is evaluated in two parts: precision, recall, and f1 scores are computed for the information retrieval part while multistimulus listening tests are used for subjective evaluation of the generated audio

Constructing narrative using a generative model and continuous action policies

This paper proposes a method for learning how to generate narrative by recombining sentences from a previous collection. Given a corpus of story events categorised into 9 topics, we approximate a deep reinforcement learning agent policy to recombine them in order to satisfy narrative structure. We also propose an evaluation of such a system. The evaluation is based on coherence, interest, and topic, in order to figure how much sense the generated stories make, how interesting they are, and examine whether new narrative topics can emerge

Personalization of object-based audio for accessibility using narrative importance

An increasing incidence of hearing impairment and of re- ported problems with broadcast audio is leading to an in- creased demand for personalized audio services. Previous research has treated these issues as a ‘speech in noise’ prob- lem; sounds are viewed as speech (good) or as competing masker (bad). This binary approach to accessible audio dis- regards the important role of some non-speech sounds in facilitating understanding of broadcast programme narra- tive. This work, as part of the S3A project, has taken a more holistic approach to audio personalization using categories of narrative importance to provide complex manipulations of broadcast audio based on narrative comprehension, instead of simply intelligibility. A simple, intuitive user-interface allows the user to adjust the complexity of audio scenes based on their personal hearing needs, metadata is generated at pro- duction using plugins to generate appropriate metadata and audio previews of user-narrative importance settings. This paper outlines the concept of narrative importance, the pro- duction tools and the end-user interface designed to deliver it. Response to these tools from target users and production staff are discussed as well as ongoing work