TY - GEN
T1 - Artspeak
T2 - 24th IEEE International Symposium on Mixed and Augmented Reality, ISMAR 2025
AU - Garnaik, Shubhangi S.R.
AU - Balasubramanian, Aruna
AU - Balasubramanian, Niranjan
AU - Ryoo, Jihoon
N1 - Publisher Copyright:
© 2025 IEEE.
PY - 2025
Y1 - 2025
N2 - Museum visits often lack personalized and interactive experiences, limiting visitor engagement with art and historical artifacts. To address this, we present ArtSpeak, a standalone augmented reality (AR) application that transforms traditional art viewing into an interactive storytelling experience. When users point their mobile cameras at an artwork, the system responds to their questions with lifelike, talking-head video narratives generated from historical portraits. However, generating such talking-head videos at runtime is computationally expensive, often requiring over a minute per response. To address this challenge, ArtSpeak introduces two major contributions. First, it employs a collection of frequently asked questions (FAQ) to generate a set of lifelike video responses for various art portraits. Second, it introduces a novel retrieval-based approach that uses GPT-based embeddings and cosine similarity to select the most relevant response. As a result, the system dynamically presents the video reply that best aligns with the user's inquiry, reducing computational overhead and ensuring a real-time, low-latency experience. More precisely, ArtSpeak achieves over 30 x lower latency and reduces energy consumption by approximately 81% compared to the real-time video generation method. User studies further validate the system's effectiveness, with 85% of participants rating the retrieved responses as relevant to their queries and 90% reporting smooth video playback. These results highlight the efficiency and user satisfaction enabled by our retrieval-based approach.
AB - Museum visits often lack personalized and interactive experiences, limiting visitor engagement with art and historical artifacts. To address this, we present ArtSpeak, a standalone augmented reality (AR) application that transforms traditional art viewing into an interactive storytelling experience. When users point their mobile cameras at an artwork, the system responds to their questions with lifelike, talking-head video narratives generated from historical portraits. However, generating such talking-head videos at runtime is computationally expensive, often requiring over a minute per response. To address this challenge, ArtSpeak introduces two major contributions. First, it employs a collection of frequently asked questions (FAQ) to generate a set of lifelike video responses for various art portraits. Second, it introduces a novel retrieval-based approach that uses GPT-based embeddings and cosine similarity to select the most relevant response. As a result, the system dynamically presents the video reply that best aligns with the user's inquiry, reducing computational overhead and ensuring a real-time, low-latency experience. More precisely, ArtSpeak achieves over 30 x lower latency and reduces energy consumption by approximately 81% compared to the real-time video generation method. User studies further validate the system's effectiveness, with 85% of participants rating the retrieved responses as relevant to their queries and 90% reporting smooth video playback. These results highlight the efficiency and user satisfaction enabled by our retrieval-based approach.
KW - Augmented Reality
KW - Cultural Heritage Interfaces
KW - FAQ Retrieval
KW - Generative AI
KW - Human-Centered AI
KW - Mobile AR Application
KW - Natural Language Interaction
UR - https://www.scopus.com/pages/publications/105025057120
U2 - 10.1109/ISMAR67309.2025.00091
DO - 10.1109/ISMAR67309.2025.00091
M3 - Conference contribution
AN - SCOPUS:105025057120
T3 - Proceedings - 2025 IEEE International Symposium on Mixed and Augmented Reality, ISMAR 2025
SP - 826
EP - 836
BT - Proceedings - 2025 IEEE International Symposium on Mixed and Augmented Reality, ISMAR 2025
A2 - Eck, Ulrich
A2 - Lee, Gun
A2 - Plopski, Alexander
A2 - Smith, Missie
A2 - Sun, Qi
A2 - Tatzgern, Markus
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 8 October 2025 through 12 October 2025
ER -