a b s t r a c t Radio production involves editing speech-based audio using tools that represent sound using simple waveforms. Semantic speech editing systems allow users to edit audio using an automatically generated transcript, which has the potential to improve the production workflow. To investigate this, we developed a semantic audio editor based on a pilot study. Through a contextual qualitative study of five professional radio producers at the BBC, we examined the existing radio production process and evaluated our semantic editor by using it to create programmes that were later broadcast.We observed that the participants in our study wrote detailed notes about their recordings and used annotation to mark which parts they wanted to use. They collaborated closely with the presenter of their programme to structure the contents and write narrative elements. Participants reported that they often work away from the office to avoid distractions, and print transcripts so they can work away from screens. They also emphasised that listening is an important part of production, to ensure high sound quality. We found that semantic speech editing with automated speech recognition can be used to improve the radio production workflow, but that annotation, collaboration, portability and listening were not well supported by current semantic speech editing systems. In this paper, we make recommendations on how future semantic speech editing systems can better support the requirements of radio production.

Interactive Audio Augmented Reality (AAR) facilitates collaborative storytelling and human interaction in participatory performance. Spatial audio enhances the auditory environment and supports real-time control of media content and the experience. Nevertheless, AAR applied to interactive performance practices remains under-explored. This study examines how audio human-computer interaction can prompt and support actions, and how AAR can contribute to developing new kinds of interactions in participatory performance.This study investigates an AAR participatory performance based on the theater and performance practice by theater maker Augusto Boal. It draws from aspects of multi-player audio-only games and interactive storytelling. A user experience study of the performance shows that people are engaged with interactive content and interact and navigate within the spatial audio content using their whole body. Asymmetric audio cues, playing distinctive content for each participant, prompt verbal and non-verbal communication. The performative aspect was well-received and participants took on roles and responsibilities within their group during the experience.

Audio Augmented Reality (AAR) consists of adding spatial audio entities into the real environment. Existing mobile applications and technologies open questions around interactive and collaborative AAR. This paper proposes an experiment to examine how spatial audio can prompt and support actions in interactive AAR experiences; how distinct auditory information influence collaborative tasks and group dynamics; and how gamified AAR can enhance participatory storytelling. We are developing an interactive multiplayer experience in AAR using the Bose Frames audio sunglasses. Four participants at a time will go through a gamified story that attempts to interfere with group dynamics. In this paper we present our AAR platform and collaborative game in terms of experience design, and detail the testing methodology and analysis that we will conduct to answer our research questions.

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When radio podcasts are produced from previously broadcast material, 30-second "thumbnails" of songs that featured in the original program are often included. Such thumbnails are made up of continuous or concatenated sections from a song and provide the audience with a summary of the music content. However, editing full-length songs down to representative thumbnails is a labor intensive process, particularly when concatenating multiple song sections. This presents an ideal application for automatic music editing tools and raises the question of how a piece of music is best summarized for this task. To gain insight into this problem we asked 120 listeners to rate the quality of thumbnails generated by eight methods (five automatic and three manual). When asked to judge overall editing quality (on a five point Likert scale) listeners gave higher ratings to methods where the edit points were quantized to bar positions, although we found no preference for structural content such as the chorus. Ratings for two automatic editing methods (one containing the chorus, one containing only the intro and outro) were not significantly different to their manual counterparts. This result suggests that the automatic editing methods applied here can be used to create production quality thumbnails.