2771-1463ISSN (Online)
2771-1471ISSN (Print)
Volume 3 , Issue 1 , PP: 36-41, 2022 | Cite this article as | XML | Html | PDF | Full Length Article
Shanthalakshmi M 1 * , Susmita Mishra 2 , LincyJemina S 3 , Raashmi P 4 , Mannuru Shalin 5 , Jananeee.v 6
Doi: https://doi.org/10.54216/JCHCI.030105
This paper focuses on providing a solution to the direct conversion of speech to shorthand. Since shorthand is not understood by many but is used for writing quick transcripts, a product is developed that converts the speech to its appropriate Gregg shorthand. A website that will be used as a front end, will use a speech-to-text API to record the speech in real-time. The converted text will then be fed into a text-to-image retrieval model that derives its corresponding Gregg shorthand for the text. The text will then be displayed to the user in real-time. By achieving this, the model reduces the need to depend upon stenographers for transcribing scripts. The resulting model achieves a good result.
Devising Stenography , Cross Modal Attention , speech shorthand , speech conversion
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