Celita is an innovative speech-recognition application developed as a two-year-long capstone project in partial fulfillment of our academic requirements for graduation. With a vision to enhance human-computer interaction, Celita utilizes speech recognition technology.
Celita aims to bridge the gap between spoken language and digital text, offering users a seamless and efficient way to interact with technology. Our project demonstrates our dedication to exploring advanced technologies and their practical applications. With Celita, we intend to contribute to the field of speech recognition while showcasing our skills and knowledge acquired during our academic journey.
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Real-time Speech Recognition: Celita can transcribe spoken words into written text in real-time, providing a practical solution for tasks like note-taking, transcription, and more.
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User-Friendly Interface: We've designed an intuitive and easy-to-navigate interface that allows users to interact with the application effortlessly, making it accessible to a wide range of individuals.
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Integration Capabilities: Our application is built with integration in mind, allowing developers to incorporate speech recognition into their own projects through a well-documented API.
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Flutter: Celita's frontend is developed using Flutter, enabling us to create a seamless and visually appealing cross-platform application.
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Firebase: We utilize Firebase's authentication and real-time database features to securely manage user accounts, settings, and customization options.
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Speech Recognition API: We harnessed the power of state-of-the-art speech recognition APIs to convert audio input into text output accurately.
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Python: The backend server for integration and additional functionalities is developed using Python, taking advantage of its robust libraries and frameworks.