Project DetailsThis work aims to develop a speech-to-text model that recognizes Torah readings with cantillation marks (Trop) and transcribes the verses accurately, including the cantillations. This model will enable the detection of reading errors and suggest corrections, thereby improving the accuracy of Torah readings.
The project focuses on developing a system capable of listening to Torah readings, identifying the spoken text, and generating an accurate transcription, including the cantillation marks. These marks are special symbols accompanying the biblical text that indicate pronunciation, intonation, and word emphasis. Advanced machine learning and neural network technologies are utilized, specifically adapted to the Hebrew language and the traditional reading of cantillations. The model is trained on datasets of recorded readings, with adjustments made to ensure precise recognition of both text and cantillations.
