Preprint Brief Report Version 1 Preserved in Portico This version is not peer-reviewed

Precision Location Keyword Detection Using Offline Speech Recognition Technique

Version 1 : Received: 6 October 2023 / Approved: 11 October 2023 / Online: 11 October 2023 (06:53:39 CEST)
Version 2 : Received: 6 November 2023 / Approved: 6 November 2023 / Online: 7 November 2023 (02:34:57 CET)

How to cite: Imam, M.; Gupta, G. Precision Location Keyword Detection Using Offline Speech Recognition Technique . Preprints 2023, 2023100690. https://doi.org/10.20944/preprints202310.0690.v1 Imam, M.; Gupta, G. Precision Location Keyword Detection Using Offline Speech Recognition Technique . Preprints 2023, 2023100690. https://doi.org/10.20944/preprints202310.0690.v1

Abstract

This study introduces an original comprehensive system centered on identifying specific terms that indicate a user's position, particularly the discrete values representing latitude and longitude. This system not only detects these terms but also retrieves the corresponding numerical data for accurate and efficient determination of locations. The importance of this endeavour encompasses various fields, notably aiding offline operations of military personnel, who often lack internet access. In such contexts, precise awareness of location is vital for strategic manoeuvres, rescue operations, and navigating unfamiliar landscapes. The system empowers these personnel by allowing them to extract exact location coordinates from spoken terms, thereby enhancing their awareness even in challenging surroundings. Apart from its military utility, the project holds broader significance. Teams responding to emergencies, personnel involved in disaster management, and exploratory missions can all gain from this technology during disruptions in communication infrastructure. Furthermore, travelers, adventurers, and outdoor enthusiasts can utilize this system to accurately determine their positions in remote areas without relying on online maps.

Keywords

Keyword Detection; Audio Models; Speech Processing

Subject

Computer Science and Mathematics, Other

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