Monika–Open-Source AI Assistant with Whisper STT and Emotional TTS

Hacker News

Hi HN, I'm sharing Monika, an open-source AI assistant I've built. The main focus was on leveraging local processing for the speech components to enhance privacy and create more natural-sounding interactions. Key components: * Speech-to-Text: Uses OpenAI's Whisper running locally. * Text-to-Speech: Uses RealtimeTTS with the Orpheus model for emotional expression, also running locally. * NLP: Uses Google Gemini on the backend It includes Voice Activity Detection (VAD) and a basic web interface using Flask. The idea was to see how well local STT and expressive local TTS could work together for a conversational agent. Tech stack: Python, Flask, Whisper, Gemini, RealtimeTTS. Video Demo: [ https://www.youtube.com/watch?v=_vdlT1uJq2k ] The project is MIT licensed. I'd appreciate any feedback, thoughts on the approach, or suggestions you might have!

Visit product View on Hacker NewsMar 31, 2025

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Product HuntOn track for Day 1 leaderboard · Strong signals: agent, model, google · Missing: mac, agents, macos

92%92% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

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Indie HackersFits the IH revenue-focused audience · Strong signals: gemini · Missing: supports, reddit linkedin, podcasting

84%84% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

56%56% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: video, google · Missing: mobile apps, ios, personal

46%46% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: interface · Missing: plus, platform, intuitive

35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

1%1% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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