Private messaging is a huge concern these days. The requirements for a perfectly private messenger are conflicting to each other and its very hard to aggregate all of them in one messenger, so even the most popular messengers like WhatsApp and Telegram are not implementing all of these requirements. In this project, we have tried to implement a messenger which meets all of the requirements for a perfectly private messenger. We have implemented all of the algorithms and protocols from scratch in Python.

Text localization in audio involves the identification and localization of relevant segments of an audio stream. This task is crucial in efficiently identifying speech segments that correspond to the words in a query text, thereby enhancing the search process. Text localization finds application in several domains, including retrieving old voice messages stored on social platforms and searching for a content in audio files such as tutorials or musics. This project provides a data processing pipeline and a system for performing text localization in audio for both English and Persian languages. By developing effective and efficient algorithms for this task, we can improve the accuracy and usability of ASR systems, generate more effective and engaging multimedia content, and augment the overall accessibility of audio-based information.

Termix is a scheduling platform for students of Sharif University of Technology. Students can select their courses and schedule their next semester based on their Program and termix will help them to find the best schedule with the least time conflicts. Termix fetch data from the university website and store them in a database. Termix is also integrated with Google Calendar and students can add their schedule to their Google Calendar.

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