TASK MAESTRO WITH SHEETS AND SPEECH RECOGNITION.
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| Title: | TASK MAESTRO WITH SHEETS AND SPEECH RECOGNITION. |
|---|---|
| Authors: | Parvathi, Varsha, Kamalapadu, B. M., Chaithra, H., Hari Krishan, R. M., Jagadish, D., Aradhana, M., Azhar Baig |
| Source: | Lex Localis: Journal of Local Self-Government; 2025 Supplement, Vol. 23 Issue S5, p3202-3209, 8p |
| Subject Terms: | DATA management, HUMAN-computer interaction, USER-centered system design, USER experience, SPEECH perception, COMPUTER performance |
| Reviews & Products: | MICROSOFT Excel (Computer software) |
| Abstract: | In contemporary data management systems, the integration of voice-controlled interfaces offers a novel approach towards facilitating data entry and manipulation. This paper presents a comprehensive framework for Excel data management leveraging voice commands. The proposed system seamlessly integrates speech recognition technology with Excel operations, enabling users to add, retrieve, and delete data through natural language interactions. Key functionalities include the addition of multiple records with customizable column names, data fetching from Excel sheets, deletion of specific records or individual cell values, all orchestrated via intuitive voice commands. A unique feature of the system is its ability to convert spoken numbers into numerical values, enhancing flexibility and user-friendliness. The efficacy of the outlined framework is exhibited through a Streamlit-based user interface, providing a user-friendly experience. Experimental evaluations showcase the system's accuracy, efficiency, and practical utility in real-world scenarios. This research paves the way for the adoption of voice-controlled interfaces in spreadsheet applications, promising enhanced productivity and accessibility in data management tasks. [ABSTRACT FROM AUTHOR] |
| Copyright of Lex Localis: Journal of Local Self-Government is the property of Institute for Local Self-Government & Public Procurement Maribor and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Complementary Index |
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