Zifan Chen
Enhanced Correction and Multi Language Support of Transcription on the "Tell your story" Digital Platform.
Rel. Luciano Lavagno, Gianpiero Cabodi. Politecnico di Torino, Master of science program in Data Science And Engineering, 2023
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Abstract
This thesis represents a pragmatic endeavor, concentrating on the application of a dynamic programming algorithm to a specific feature of the web platform, [Tell your story](https://tiraccontounastoria.org/st/). "Tell your story" is a digital platform that serves a crucial societal function by preserving, sharing, and listening to individuals' lifetime memories. It is engineered to reestablish the significance of personal experiences, particularly for the elderly, by alleviating their isolation and aiding in memory recall. It also allows relatives and friends to explore and uncover specific details within these oral stories. The platform incorporates an interview system that automatically records stories via voice messages. Users can record their stories as brief or detailed voice messages, either in response to a series of questions or in an unrestricted format.
As individuals engage with the stories, the audio is broadcasted on the website, and concurrently, an audio transcription is displayed to enhance comprehension and sharing
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