Publications

@inproceedings{su_sonifyar_2024,

title = {SonifyAR: Context-Aware Sound Effect Generation in Augmented Reality},

author = {X. Su and E. Koh and C. Xiao},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85194146678&doi=10.1145%2f3613905.3650927&partnerID=40&md5=fa2154e1ffdd5339696ccb39584dee16},

doi = {10.1145/3613905.3650927},

isbn = {979-840070331-7 (ISBN)},

year  = {2024},

date = {2024-01-01},

booktitle = {Conf Hum Fact Comput Syst Proc},

publisher = {Association for Computing Machinery},

abstract = {Sound plays crucial roles in enhancing user experience and immersiveness in Augmented Reality (AR). However, current AR authoring platforms lack support for creating sound effects that harmonize with both the virtual and the real-world contexts. In this work, we present SonifyAR, a novel system for generating context-aware sound effects in AR experiences. SonifyAR implements a Programming by Demonstration (PbD) AR authoring pipeline. We utilize computer vision models and a large language model (LLM) to generate text descriptions that incorporate context information of user, virtual object and real world environment. This context information is then used to acquire sound effects with recommendation, generation, and retrieval methods. The acquired sound effects can be tested and assigned to AR events. Our user interface also provides the flexibility to allow users to iteratively explore and fine-tune the sound effects. We conducted a preliminary user study to demonstrate the effectiveness and usability of our system. © 2024 Association for Computing Machinery. All rights reserved.},

keywords = {'current, Augmented Reality, Augmented reality authoring, Authoring Tool, Context information, Context-Aware, Immersiveness, Iterative methods, Mixed reality, Real-world, Sound, Sound effects, User interfaces, Users' experiences},

pubstate = {published},

tppubtype = {inproceedings}

}