Organizational Unit:
Sonification Lab

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Start date: 2020 × End date: 2023 × Author: Nadri, Chihab ×

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Now showing 1 - 4 of 4
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    NEURODIVERGENCE IN SOUND: SONIFICATION AS A TOOL FOR MENTAL HEALTH AWARENESS
    (Georgia Institute of Technology, 2023-06) Nadri, Chihab ; Al Mater, Hamza ; Morrison, Spencer ; Tiemann, Allison ; Song, Inuk ; Lee, Tae Ho ; Jeon, Myounghoon
    The need to build greater mental health awareness as an important factor in decreasing stigma surrounding individuals with neurodivergent conditions has led to the development of programs and activities that seek to increase mental health awareness. Using a sonification approach with neural activity can effectively convey an individual’s psychological and mental characteristics in a simple and intuitive manner. In this study, we developed a sonification algorithm that alters existing music clips according to fMRI data corresponding to the salience network activity from neurotypical and neurodivergent individuals with schizophrenia. We conducted an evaluation of these sonifications with 24 participants. Results indicate that participants were able to differentiate between sound clips stemming from different neurological conditions and that participants gained increased awareness of schizophrenia through this brief intervention. Findings indicate sonification could be an effective tool in raising mental health awareness and relate neurodivergence to a neurotypical audience.
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    Preliminary evaluation of lead time variation for rail crossing in-vehicle alerts
    (Georgia Institute of Technology, 2022-06) Nadri, Chihab ; Zieger, Scott ; Lautala, Pasi ; Nelson, David ; Jeon, Myounghoon
    In-Vehicle Auditory Alert (IVAA) effectiveness depends on several auditory factors. Lead time has been shown to significantly influence IVAA effectiveness for automotive displays, although applications for Highway-Rail Grade Crossings (HRGCs) have yet to modulate and determine an appropriate lead time. To address this research gap, we conducted a small-scale driving simulator study to investigate the effect of lead time variation on driving performance and gaze behavior at rail crossings. We recruited 11 participants who drove through three experimental drives with different alert state conditions. Preliminary results show that a seven second lead time led to statistically higher temporal demand, a slower approach speed to crossings, and better gaze behavior than the no IVAA condition. The seven second lead time condition had similar higher values than the advanced warning condition, although they were not statistically significant. Findings of the current study offer insight into auditory display guidance for HRGCs, although future work involving a larger recruitment pool is needed to confirm study findings.
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    Investigating the effect of earcon and speech variables on hybrid auditory alerts at rail crossings
    (Georgia Institute of Technology, 2021-06) Nadri, Chihab ; Lee, Seul Chan ; Kekal, Siddhant ; Li, Yinjia ; Li, Xuan ; Lautala, Pasi ; Nelson, David ; Jeon, Myounghoon
    Despite rail industry advances in reducing accidents at Highway Rail Grade Crossings (HRGCs), train-vehicle collisions continue to happen. The use of auditory displays has been suggested as a countermeasure to improve driver behavior at HRGCs, with prior research recommending the use of hybrid sound alerts consisting of earcons and speech messages. In this study, we sought to further investigate the effect of auditory variables in hybrid sound alerts. Nine participants were recruited and instructed to evaluate 18 variations of a hybrid In-Vehicle Auditory Alert (IVAA) along 11 subjective ratings. Results showed that earcon speed and pitch contour design can change user perception of the hybrid IVAA. Results further indicated the influence of speech gender and other semantic variables on user assessment of HRGC IVAAs. Findings of the current study can also inform and instruct the design of appropriate hybrid IVAAs for HRGCs.
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    Introduction of a computational modelling approach to auditory display research: Case studies using the QN-MHP framework
    (Georgia Institute of Technology, 2021-06) Jeon, Myounghoon ; Nadri, Chihab ; Zhang, Yiqi
    For more than two decades, a myriad of design and research methods have been proposed in the ICAD community. Neurological methods have been presented since the inception of ICAD, and psychological human-subjects research has become as a legitimate approach to auditory display design and evaluation. However, little research has been conducted on modelling approaches to formalize human behavior in response to auditory displays. To bridge this gap, the present paper introduces computational modelling in auditory displays using the Queuing Network- Model Human Processor (QN-MHP) framework. After delineating the advantages of computational modelling and the QN-MHP framework, the paper introduces four case studies, which modelled drivers' behavior in response to invehicle auditory warnings, followed by the implications and future work. We hope that this paper can spark lively discussions on computational modelling in the ICAD community and thus, more researchers can benefit from using this method for future research.