Record Once, Post Everywhere: Automatic Shortening of Audio Stories for Social Media

Abstract

Following the prevalence of short-form video, short-form voice content has emerged on social media platforms like Twitter and Facebook. A challenge that creators face is hard constraints on the content length. If the initial recording is not short enough, they need to re-record or edit their content. Both are time-consuming, and the latter, if supported, can have a learning curve. Moreover, creators need to manually create multiple versions to publish content on platforms with different length constraints. To simplify this process, we present ROPE1 (Record Once, Post Everywhere). Creators can record voice content once, and our system will automatically shorten it to all length limits by removing parts of the recording for each target. We formulate this as a combinatorial optimization problem and propose a novel algorithm that automatically selects optimal sentence combinations from the original content to comply with each length constraint. Creators can customize the algorithmically shortened content by specifying sentences to include or exclude. Our system can also use the user-specified constraints to recompute and provides a new version. We conducted a user study comparing ROPE with a sentence-based manual editing baseline. The results show that ROPE can generate high-quality edits, alleviating the cognitive loads of creators for shortening content. While our system and user study address short-form voice content specifically, we believe that the same concept can also be applied to other media such as video with narration and dialog.