Soundify: Matching Sound Effects to Video

Autor:	Lin, David Chuan-En, Germanidis, Anastasis, Valenzuela, Cristóbal, Shi, Yining, Martelaro, Nikolas
Rok vydání:	2021
Předmět:	Computer Science - Sound Computer Science - Computer Vision and Pattern Recognition Computer Science - Human-Computer Interaction Computer Science - Multimedia Electrical Engineering and Systems Science - Audio and Speech Processing
Druh dokumentu:	Working Paper
DOI:	10.1145/3586183.3606823
Popis:	In the art of video editing, sound helps add character to an object and immerse the viewer within a space. Through formative interviews with professional editors (N=10), we found that the task of adding sounds to video can be challenging. This paper presents Soundify, a system that assists editors in matching sounds to video. Given a video, Soundify identifies matching sounds, synchronizes the sounds to the video, and dynamically adjusts panning and volume to create spatial audio. In a human evaluation study (N=889), we show that Soundify is capable of matching sounds to video out-of-the-box for a diverse range of audio categories. In a within-subjects expert study (N=12), we demonstrate the usefulness of Soundify in helping video editors match sounds to video with lighter workload, reduced task completion time, and improved usability. Comment: https://soundify.cc
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2112.09726 Zobrazit plný text záznamu View this record from Arxiv