
Worked on the lemonade-sdk/lemonade repository to deliver real-time speech-to-text transcription for chat, enabling users to see live transcriptions and automatically send messages upon recording completion. Leveraged React, JavaScript, and TypeScript to implement end-to-end audio processing, including voice activity detection and model selection, while refactoring transcription logic into reusable hooks for maintainability. Developed URL-based chatbot prompt integration, allowing prompts to be extracted from query parameters and applied to streamline chat workflows. Improved frontend architecture by isolating ASR fetch logic and using constants, resulting in a more scalable and testable codebase. Collaborated on features prepared for QA and downstream integration.
March 2026 monthly summary for lemonade SDK. Delivered real-time speech-to-text transcription UX for chat and URL-based chatbot prompt integration, delivering significant enhancements to user efficiency and chat accuracy. Implemented end-to-end STT for chat with real-time transcription display, auto-send on recording completion, and robust audio processing (vad-based stop, trim fixes, model selection). Added ability to extract and apply prompts from URL query parameters to streamline chatbot workflows and adjust input focus. Undertook frontend architecture improvements to improve maintainability and performance, including refactoring transcription logic into reusable hooks, using constants, and isolating ASR fetch logic. Business value: faster, hands-free chat experiences, smoother onboarding and integration with external prompts, scalable frontend with clearer abstractions.
March 2026 monthly summary for lemonade SDK. Delivered real-time speech-to-text transcription UX for chat and URL-based chatbot prompt integration, delivering significant enhancements to user efficiency and chat accuracy. Implemented end-to-end STT for chat with real-time transcription display, auto-send on recording completion, and robust audio processing (vad-based stop, trim fixes, model selection). Added ability to extract and apply prompts from URL query parameters to streamline chatbot workflows and adjust input focus. Undertook frontend architecture improvements to improve maintainability and performance, including refactoring transcription logic into reusable hooks, using constants, and isolating ASR fetch logic. Business value: faster, hands-free chat experiences, smoother onboarding and integration with external prompts, scalable frontend with clearer abstractions.

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