TY - GEN
T1 - Artificial Intelligence and Home Music Listening An
T2 - 19th International Audio Mostly Conference, Audio Mostly 2024
AU - Melder, Trinity
AU - Savery, Richard
N1 - Publisher Copyright:
© 2024 Owner/Author.
PY - 2024/9/18
Y1 - 2024/9/18
N2 - This study explores the transformative role of artificial intelligence (AI) in enhancing home music listening experiences. We analyzed 96 academic papers to assess AI's evolution, impact, and technological integration in-home music systems by integrating qualitative and quantitative research methods. Our findings highlight the extensive use of AI in personalizing music experiences through recommendation algorithms and adaptive audio processing, which have significantly improved user interaction and satisfaction. The research identified key trends in AI deployment, revealing a strong focus on enhancing accessibility and user engagement. However, the study also pinpointed substantial gaps, particularly in music's emotional and contextual adaptation, suggesting potential areas for future development. This paper contributes to understanding AI's pivotal role in evolving home music listening and proposes directions for future research to bridge identified gaps.
AB - This study explores the transformative role of artificial intelligence (AI) in enhancing home music listening experiences. We analyzed 96 academic papers to assess AI's evolution, impact, and technological integration in-home music systems by integrating qualitative and quantitative research methods. Our findings highlight the extensive use of AI in personalizing music experiences through recommendation algorithms and adaptive audio processing, which have significantly improved user interaction and satisfaction. The research identified key trends in AI deployment, revealing a strong focus on enhancing accessibility and user engagement. However, the study also pinpointed substantial gaps, particularly in music's emotional and contextual adaptation, suggesting potential areas for future development. This paper contributes to understanding AI's pivotal role in evolving home music listening and proposes directions for future research to bridge identified gaps.
KW - Artificial Intelligence
KW - Home Music Systems
KW - Music Personalization
UR - https://www.scopus.com/pages/publications/85204942519
UR - https://audiomostly.com/2024/
U2 - 10.1145/3678299.3678330
DO - 10.1145/3678299.3678330
M3 - Conference contribution
AN - SCOPUS:85204942519
T3 - ACM International Conference Proceeding Series
SP - 318
EP - 324
BT - Proceedings of the 19th International Audio Mostly Conference, Audio Mostly 2024
A2 - Ludovico, Luca Andrea
A2 - Mauro, Davide Andrea
PB - Association for Computing Machinery, Inc
Y2 - 18 September 2024 through 20 September 2024
ER -