Listener: improving news experience with AI-added context, text-to-speech, and sentiment analysis
In today’s digital landscape, the deluge of news sources presents a significant obstacle for users seeking to access pertinent information efficiently. Listener is an innovative web application poised to revolutionize the news consumption experience by leveraging cutting-edge AI technologies. Listen...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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Nanyang Technological University
2024
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| Online Access: | https://hdl.handle.net/10356/175149 |
| _version_ | 1826127446378807296 |
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| author | Heng, Wei Jie |
| author2 | Owen Noel Newton Fernando |
| author_facet | Owen Noel Newton Fernando Heng, Wei Jie |
| author_sort | Heng, Wei Jie |
| collection | NTU |
| description | In today’s digital landscape, the deluge of news sources presents a significant obstacle for users seeking to access pertinent information efficiently. Listener is an innovative web application poised to revolutionize the news consumption experience by leveraging cutting-edge AI technologies. Listener is meticulously crafted to mitigate the challenges of information overload, offering users a streamlined and personalized approach to news consumption. At the core of Listener’s functionality lies the integration of advanced AI tools, prominently featuring OpenAI’s gpt-3.5-turbo for robust content summarization and contextual enrichment. This distill complex news articles into concise summaries while providing additional context that users may seek to further their understanding. Moreover, OpenAI’s text-to-speech functionality, facilitate seamless auditory consumption of news content. This feature not only caters to users with visual impairments but also enhances multitasking capabilities, allowing individuals to consume news on the go or while engaging in other activities. In conclusion, Listener represents how AI can be used to further enrich the news consumption experience with all these new technologies. |
| first_indexed | 2024-10-01T07:09:01Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/175149 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:09:01Z |
| publishDate | 2024 |
| publisher | Nanyang Technological University |
| record_format | dspace |
| spelling | ntu-10356/1751492024-04-26T15:41:04Z Listener: improving news experience with AI-added context, text-to-speech, and sentiment analysis Heng, Wei Jie Owen Noel Newton Fernando School of Computer Science and Engineering OFernando@ntu.edu.sg Computer and Information Science News aggregation gpt Text-to-speech In today’s digital landscape, the deluge of news sources presents a significant obstacle for users seeking to access pertinent information efficiently. Listener is an innovative web application poised to revolutionize the news consumption experience by leveraging cutting-edge AI technologies. Listener is meticulously crafted to mitigate the challenges of information overload, offering users a streamlined and personalized approach to news consumption. At the core of Listener’s functionality lies the integration of advanced AI tools, prominently featuring OpenAI’s gpt-3.5-turbo for robust content summarization and contextual enrichment. This distill complex news articles into concise summaries while providing additional context that users may seek to further their understanding. Moreover, OpenAI’s text-to-speech functionality, facilitate seamless auditory consumption of news content. This feature not only caters to users with visual impairments but also enhances multitasking capabilities, allowing individuals to consume news on the go or while engaging in other activities. In conclusion, Listener represents how AI can be used to further enrich the news consumption experience with all these new technologies. Bachelor's degree 2024-04-22T05:25:56Z 2024-04-22T05:25:56Z 2024 Final Year Project (FYP) Heng, W. J. (2024). Listener: improving news experience with AI-added context, text-to-speech, and sentiment analysis. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/175149 https://hdl.handle.net/10356/175149 en application/pdf Nanyang Technological University |
| spellingShingle | Computer and Information Science News aggregation gpt Text-to-speech Heng, Wei Jie Listener: improving news experience with AI-added context, text-to-speech, and sentiment analysis |
| title | Listener: improving news experience with AI-added context, text-to-speech, and sentiment analysis |
| title_full | Listener: improving news experience with AI-added context, text-to-speech, and sentiment analysis |
| title_fullStr | Listener: improving news experience with AI-added context, text-to-speech, and sentiment analysis |
| title_full_unstemmed | Listener: improving news experience with AI-added context, text-to-speech, and sentiment analysis |
| title_short | Listener: improving news experience with AI-added context, text-to-speech, and sentiment analysis |
| title_sort | listener improving news experience with ai added context text to speech and sentiment analysis |
| topic | Computer and Information Science News aggregation gpt Text-to-speech |
| url | https://hdl.handle.net/10356/175149 |
| work_keys_str_mv | AT hengweijie listenerimprovingnewsexperiencewithaiaddedcontexttexttospeechandsentimentanalysis |