Transcription App for Multilingual Meetings

Enhanced Project Proposal: Speech-to-Text Transcription Application for Legal Depositions 1. Project Overview This project aims to develop a user-friendly, stand-alone application (with potential future web deployment) specifically designed to streamline the workflow of legal professionals conducting depositions. The application will leverage robust speech-to-text technology to generate accurate transcripts for legal proceedings in both English, accuracy is very important. 2. Key Features • Multi-lingual Speech Recognition: Integrate with a high-fidelity speech recognition engine, ideally Deepgram, capable of accurately transcribing spoken English and Spanish legal proceedings. • Real-Time Streaming and Recording: Offer seamless live transcription functionalities for meetings conducted across various platforms like Zoom and Microsoft Teams. Support for additional platforms with streaming audio capabilities can be explored. • Dual Transcript View with Interactive Playback: o Read-Only Transcript: Display a real-time, read-only transcript for reference during the deposition. Integrate this transcript with the audio recording via a JSON file. Clicking on a word in the transcript should trigger playback of the corresponding audio segment, allowing users to easily revisit specific parts of the deposition. o Editable Transcript: Provide a separate live transcript window where users can make real-time edits and annotations as the deposition unfolds. • Pre-recorded Audio File Transcription: Allow users to upload pre-recorded audio files in various formats for accurate transcription, even if the recording wasn't conducted using the application's live streaming feature. • Implement a user authentication mechanism requiring users to enter a valid password or license number upon application launch. 3. Technical Specifications • Programming Language: Python (preferred) • Speech Recognition Engine: Deepgram (open to discussion on alternative solutions) • Development Environment: PyCharm IDE (preferred) • API Integrations (Optional): Integration with Google Calendar API can be explored for potential workflow enhancements. While not required for core functionality, consider exploring API integrations with Zoom and Microsoft Teams to simplify meeting access and transcription initiation. • Additional Libraries: Utilize libraries for efficient JSON data handling, audio playback functionalities, and user interface development. 4. Ideal Candidate Skills • Proven experience in speech recognition software development using Deepgram or similar technologies. • Expertise in language processing, particularly in handling legal terminology for both English and Spanish. • Strong understanding of API integrations, particularly with Google Calendar (optional) and potentially Zoom/Microsoft Teams APIs (optional). • Excellent User Interface (UI) development experience to create a user-friendly and intuitive application for legal professionals. 5. Deliverables • A fully functional speech-to-text application for legal depositions with the features outlined above. • Stand-alone application initially, with potential future web deployment options to be discussed. • Ongoing support and maintenance for bug fixes and future enhancements. 6. Client Background While I have limited programming experience, I have some familiarity with the Deepgram API in Python using PyCharm. This approach would be preferred if feasible for this project. 7. Next Steps • Engage in detailed discussions to refine project scope and feasibility. • Define specific user stories and workflows to ensure the application effectively meets the needs of legal professionals. • Develop a comprehensive technical implementation plan outlining the development process. • Establish a realistic development timeline and budget. This enhanced project proposal provides a more comprehensive overview of the envisioned application's functionalities and technical specifications. By partnering with a skilled developer who possesses the necessary expertise, this application has the potential to become a valuable tool for legal professionals, significantly enhancing efficiency and accuracy in managing and transcribing legal depositions.