Browsing by Author "Siddiqui, Arsh"

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  • Audio augmented reality using sonification to enhance visual art experiences: Lessons learned
    Dam, Abhraneil; Lee, YeaJi; Siddiqui, Arsh; Lages, Wallace Santos; Jeon, Myounghoon (Academic Press – Elsevier, 2024-11)
    Augmenting visual art in art galleries can be an effective Audio Augmented Reality (AAR) application for indoor exploration. In the current study, eight paintings from four genres were augmented with audio through their sonification. Basic Audio was generated using a sonification algorithm by identifying the major colors of the paintings, and Enhanced Audio was generated by a musician enhancing the Basic Audio; these were presented with the paintings to compare against No Audio. Twenty-six participants viewed each painting in all three conditions; eye gaze metrics, and qualitative data were collected. Results showed that Enhanced Audio led to significantly greater engagement and positive sentiments, compared to Basic Audio. Thematic analysis showed semantic and syntactic relationships of the audio with the paintings, and a tendency to guide users’ gaze over time. Findings from this study can guide future AAR developments to improve auditory display designs to enhance visual experiences.
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    Enhancing Art Gallery Visitors' Experiences through Audio Augmented Reality Technology
    Dam, Abhraneil; Lee, Yeaji; Siddiqui, Arsh; Lages, Wallace Santos; Jeon, Myounghoon (SAGE, 2023-11-23)
    Audio Augmented Reality (AAR) applications are gaining traction, especially for entertainment purposes. To that extent, the current study explored its use and effectiveness in enhancing art gallery visitors’ experiences. Four paintings were selected and sonified using the Jython algorithm to produce computer generated music (Basic AAR); the audio was then further enhanced with traditional music by a musician (Enhanced AAR). Twenty-six participants experienced each painting in Basic, Enhanced, and No AAR condition. Results show that AAR cues had a significant effect on participants’ subjective feedback towards the paintings. Sentiment Analysis shows that participants mentioned significantly more positive words from Enhanced AAR than the others. Enhanced AAR also made participants express a sense of immersion, whereas Basic AAR made them concentrate more on forlorn aspects of the paintings. Findings from this study suggest ways to improve and customize AAR cues for different painting styles, and indicate the need for multi-modal augmentations.
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    Extracting a Definition and Taxonomy for Audio Augmented Reality (AAR) Using Grounded Theory
    Dam, Abhraneil; Siddiqui, Arsh; Leclerq, Charles; Jeon, Myounghoon (SAGE, 2022-10-27)
    The concept of Augmented Reality (AR) has evolved over the years since its inception in 1957. However, as of today, AR is mostly realized using a visual medium. Almost all applications of AR rely on the user’s ability to see. A few recent works have attempted to explore a new modality for AR–e.g., audio. However, the concept of using audio to augment reality has been considered debatable and there is no specific definition of the concept. To better understand this new concept, we launched a study using Grounded Theory to develop a definition and taxonomy for the concept of Audio Augmented Reality (AAR). This paper shares the preliminary results based on the activities conducted thus far, and hopes to generate discussion on using audio to augment reality within the Human Factors community.
  • Taxonomy and definition of audio augmented reality (AAR): A grounded theory study
    Dam, Abhraneil; Siddiqui, Arsh; Leclercq, Charles; Jeon, Myounghoon (Academic Press - Elsevier, 2024-02)
    AR applications have mostly considered visual augmentations while excluding other modalities. Recent developments in audio augmented reality (AAR) applications have been based on the definitions of visual AR or mixed reality (MR), and thus, AAR technology development has lacked systematic efforts. We investigated the concept of augmented reality through audio to provide a systematic understanding and generate a taxonomy and a definition for AAR. A conference workshop (N = 28), focus groups (N = 18), and expert interviews (N = 6) generated qualitative data regarding the concept of AAR. Grounded Theory (GT) was used to analyze the data and produce a new taxonomy and a definition. The AAR taxonomy consists of three categories – Environment Connected, Goal Directed, and Context Adapted, with three subcategories respectively. The need for a separate taxonomy for AAR is highlighted to aid in the development of AAR applications in a systematic manner. The taxonomy is expected to be used as a heuristic tool that can guide developers to build AAR applications and can be used in evaluating user experience with AAR applications.