Library Hi Tech News Transforming Wikipedia text into audio through machine learning
Type
Publication
Authors
Category
Project
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Publication Year
2024
Volume
ahead-of-print
Subject
General
Series Name
Abstract
Purpose: The purpose of this study is to navigate the process of transforming Wikipedia articles into audio files for library readers. The system provides a feasible manner of listening to Wikipedia content, accommodating diverse learning preferences and enlarging knowledge in education society. Design/methodology/approach:This framework has been constructed using the Python programming languages in the Linux operating platform. Application programming interface and Google text-to-speech (TTS) are required as additional software packages to design this prototype system. Transform any Wikipedia pages into audio files through Wikitrola for libraries and information centers. Wikipedia articles are directly transformed into audio, as these integrate the content seamlessly for the user experience. The whole system has been designed and configured on the basis of machine learning to provide dynamic services among the readers. Findings: The viewer could use the machine learning system to turn Wikipedia articles into audio files, allowing them to listen to Wikipedia content in audio format. This would make information more accessible and adaptable to diverse learning modes, allowing written content to be engaged in novel and visionary ways. Originality/value: The insightful observation in connection with the paper is that it shows how to convert text-based material into audio through the Google TTS and machine learning Python programming and finally incorporate them in Wikipedia articles. A harmonious system of information dissemination and technical education is established. This approach shows the effectiveness of imagination and the use of programming tools to enhance learning and knowledge-seeking processes.
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Biblio Notes
Mandal, S. (2024). Transforming Wikipedia text into audio through machine learning. Library Hi Tech News, ahead-of-print(ahead-of-print). https://doi.org/10.1108/LHTN-07-2024-0111
Number of Copies
1
Library | Accession No | Call No | Copy No | Edition | Location | Availability |
---|---|---|---|---|---|---|
Main | 27 | 1 | Yes |