Audio stories are an engaging form of communication that combine speech and music into compelling narratives. Existing audio editing tools force story producers to manipulate speech and music tracks via tedious, low-level waveform editing. In contrast, we present a set of tools that analyze the audio content of the speech and music and thereby allow producers to work at much higher level. Our tools address several challenges in creating audio stories, including (1) navigating and editing speech, (2) selecting appropriate music for the score, and (3) editing the music to complement the speech. Key features include a transcript-based speech editing tool that automatically propagates edits in the transcript text to the corresponding speech track; a music browser that supports searching based on emotion, tempo, key, or timbral similarity to other songs; and music retargeting tools that make it easy to combine sections of music with the speech. We have used our tools to create audio stories from a variety of raw speech sources, including scripted narratives, interviews and political speeches. Informal feedback from first-time users suggests that our tools are easy to learn and greatly facilitate the process of editing raw footage into a final story.
REF present an interface for editing audio stories like interviews and speeches, which includes transcriptbased speech editing, music browsing, and music retargeting.
Content-based tools for editing audio stories
UIST '13
Computer Science