Vision to Voice Object Detection with Real-Time Audio Assistance

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Bhumireddi Harish; T. Anusha; Gandreti Sneha; Botta Vasavi Anusha; Kolipaka Keerthana; Gollamala Saiteja

Vision to Voice Object Detection with Real-Time Audio Assistance

Authors: Bhumireddi Harish, T. Anusha, Gandreti Sneha, Botta Vasavi Anusha, Kolipaka Keerthana, Gollamala Saiteja

Unique Paper ID: 175924
Volume: 11
Issue: 11
PageNo: 5039-5046

Keywords: Vision to Voice YOLOv8 Real-time Voice Assistance Blinded Assistance AI Navigation Accessibility Image Localization Data Augmentation PyTorch Edge Devices Auditory Feedback Smart Navigation Personalized Audio Guidance.

Abstract:
Vision to Voice uses the YOLOv8 algorithm for object detection which provides real-time auditory assistance to the blind and presents the environment in vocal form. Navigating through such system enhances accessibility and inclusion due to environmental cues' vocalization, smart navigation, and image processing in real time. Thus, it gives a better chance for the visually impaired to operate with audio guidance and speech feedback in their daily lives. This system makes the user feel confident in navigating complex environments by upgrading the contextual awareness balanced between human and environment interaction through deep learning and image localization. This paper aims at discussing architecture and features of YOLOv8, thereby elaborating on its achievements as compared to its previous versions. YOLOv8 with its next-generation backbone for effective feature extraction joined with another refinement for better localizing objects within the neck and anchor-free detection for better performance and flexibility. State-of-the-art augmentations such as mosaic augmentation and adaptive training strategies on the model greatly improve robustness and generalization across various datasets. YOLOv8 provides framework alternatives through PyTorch, increasing portability and allowing customization of the code for deployment on other platforms like edge devices. Experimental results have demonstrated the model's efficacy in tireless real-world applications such as assistive technologies, autonomous navigation, video surveillance, industrial automation, and healthcare.

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Cite This Article

ISSN: 2349-6002
Volume: 11
Issue: 11
PageNo: 5039-5046

Vision to Voice Object Detection with Real-Time Audio Assistance

Available:https://ijirt.org/article?manuscript=175924

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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