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Priambudi Lintang Bagaskara

dblp:374/9517 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2024
0009-0003-0359-2152ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Human-AI interaction · 100%
Computer graphics and multimedia
1 paper
Audio and music processing · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Human-AI interaction › generative AI
generative AI in creative practice
0.812024
Sound Designer-Generative AI Interactions: Towards Designing Creative Support Tools for Professional Sound Designers · CHI 2024
Audio and music processing
sound design
0.212024
Sound Designer-Generative AI Interactions: Towards Designing Creative Support Tools for Professional Sound Designers · CHI 2024

Methods — techniques the papers use, named apart from their topics

semi-structured interviews · 1.5interactive generative AI models · 1.5
YearPublicationVenuePosition
2024 Sound Designer-Generative AI Interactions: Towards Designing Creative Support Tools for Professional Sound Designers
abstract
The practice of sound design involves creating and manipulating environmental sounds for music, films, or games. Recently, an increasing number of studies have adopted generative AI to assist in sound design co-creation. Most of these studies focus on the needs of novices, and less on the pragmatic needs of sound design practitioners. In this paper, we aim to understand how generative AI models might support sound designers in their practice. We designed two interactive generative AI models as Creative Support Tools (CSTs) and invited nine professional sound design practitioners to apply the CSTs in their practice. We conducted semi-structured interviews and reflected on the challenges and opportunities of using generative AI in mixed-initiative interfaces for sound design. We provide insights into sound designers’ expectations of generative AI and highlight opportunities to situate generative AI-based tools within the design process. Finally, we discuss design considerations for human-AI interaction researchers working with audio.
Purnima Kamath, Fabio Morreale, Priambudi Lintang Bagaskara, Yize Wei, Suranga Nanayakkara
CHI3