Training birdsong recognition using virtual reality
Background: In mega-biodiverse environments, where different species are more likely to be heard than seen, species monitoring is generally performed using bioacoustics methodologies. Furthermore, since bird vocalizations are reasonable estimators of biodiversity, their monitoring is of great import...
Guardado en:
Autores principales: | , , |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
KeAi Communications Co., Ltd.
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/339eaa32d9d9474094ae1dd51bd3f79d |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Sumario: | Background: In mega-biodiverse environments, where different species are more likely to be heard than seen, species monitoring is generally performed using bioacoustics methodologies. Furthermore, since bird vocalizations are reasonable estimators of biodiversity, their monitoring is of great importance in the formulation of conservation policies. However, birdsong recognition is an arduous task that requires dedicated training in order to achieve mastery, which is costly in terms of time and money due to the lack of accessibility of relevant information in field trips or even specialized databases. Immersive technology based on virtual reality (VR) and spatial audio may improve species monitoring by enhancing information accessibility, interaction, and user engagement. Methods: This study used spatial audio, a Bluetooth controller, and a head-mounted display (HMD) to conduct an immersive training experience in VR. Participants moved inside a virtual world using a Bluetooth controller, while their task was to recognize targeted birdsongs. We measured the accuracy of recognition and user engagement according to the User Engagement Scale. Results: The experimental results revealed significantly higher engagement and accuracy for participants in the VR-based training system than in a traditional computer-based training system. All four dimensions of the user engagement scale received high ratings from the participants, suggesting that VR-based training provides a motivating and attractive environment for learning demanding tasks through appropriate design, exploiting the sensory system, and virtual reality interactivity. Conclusions: The accuracy and engagement of the VR-based training system were significantly high when tested against traditional training. Future research will focus on developing a variety of realistic ecosystems and their associated birds to increase the information on newer bird species within the training system. Finally, the proposed VR-based training system must be tested with additional participants and for a longer duration to measure information recall and recognition mastery among users. |
---|