An on-device AI teleprompter that listens to your conversations and suggests charismatic quotes in real-time.
Tele-Prompter is an on-device AI application that listens to your conversations during meetings and suggests charismatic quotes in real-time. It helps users become more engaging speakers by providing contextually relevant phrases without requiring cloud services. The tool processes audio locally using speech recognition and AI models to maintain complete privacy.
Professionals, presenters, and anyone who participates in meetings and wants to improve their conversational charisma through AI-assisted suggestions.
Developers choose Tele-Prompter because it offers complete privacy through on-device processing, provides real-time conversational enhancements, and is open-source with extensible architecture for custom improvements.
Tele-Prompter is an AI-powered application that runs locally on your device to enhance your conversational charisma during meetings. It listens to your speech and provides relevant, engaging quotes to help you express yourself more effectively.
hear library) to transcribe your speech without cloud dependencies.Tele-Prompter believes that AI should enhance human communication without compromising privacy, running entirely on-device to keep conversations secure while helping users become more engaging speakers.
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All audio processing and AI inference occur locally on your device, as highlighted in the README, ensuring no data is transmitted to external servers and maintaining complete conversation privacy.
Analyzes speech in real-time to suggest charismatic quotes during meetings, helping users improve engagement and expressiveness without delays, as demonstrated in the provided demo video.
Supports both semantic embeddings for general use and an experimental fine-tuned language model, offering users a choice between reliability and advanced, context-aware suggestions.
The project is open-source, allowing developers to modify and extend it—for example, by adding Whisper for cross-platform speech recognition, as suggested in the README.
Currently only works on MacOS due to dependency on the `hear` library for on-device speech recognition, severely limiting accessibility for Windows or Linux users.
Requires installations of conda, transformers, and torch, which can be cumbersome and error-prone for users not familiar with Python environments or deep learning frameworks.
The fine-tuned model is labeled 'highly experimental' in the README, meaning it may produce inconsistent or unreliable suggestions, making it unsuitable for critical or professional use cases.