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1 points·by siim·2 ay önce·0 comments

Show HN: VoxConvo – "X but it's only voice messages"

voxconvo.com
10 points·by siim·8 ay önce·16 comments

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siim
·8 ay önce·discuss
Speaking > typing for creation.

Reading > listening for consumption.

Talk to create, read to consume.
siim
·8 ay önce·discuss
Curious what made you think the backend uses LLMs for content generation?

To clarify:

1. transcription is local VOSK speech-to-text via WebSocket

2. live transcript post-processing has optional Gemini Flash-lite turned on which tries to fix obvious transcription mistakes, nothing else. The real fix here is more accurate transcriber.

3. backend: TypeGraphQL + MongoDB + Redis

The anti-AI stance isn't "zero AI anywhere", it's about requiring human input.

AI-generated audio is either too bad or too perfect. Real recorded voice has human imperfections.
siim
·8 ay önce·discuss
That's a good call. While there's no general public feed, individual profiles are public. For example, here's mine: https://voxconvo.com/siim
siim
·8 ay önce·discuss
True. However making voice input has higher friction than typing chatgpt write me a reply.
siim
·9 ay önce·discuss
I'm working on https://X11.Social, a voice-first content creation tool for X.

The initial idea was "call to tweet", the ability to compose posts on the go by having a natural conversation with an AI assistant over a simple phone call. This is useful for turning thoughts from a walk or drive into a polished "brain dump" post, or for engaging with user lists without being at a computer.

It has since evolved into a broader system:

Chrome Extension: A context-aware assistant that lives in the browser. It has a Quake-style console (activated by opt+space) for quick chat and can analyze the content of any page you're on (e.g., YouTube transcripts, articles, other tweets) to help you create relevant content.

Engagement Predictor: A feature that scores tweet drafts in real-time to predict their potential for engagement. It's built on a model trained on my own dataset pulled from the X API and other public dataset from Kaggle[0].

Scheduled AI Calls: The system can call you on a predefined schedule to proactively brainstorm content ideas.

Here is the tech stack:

- Frontend: React, Tailwind, shadcn/ui

- Auth: X OAuth

- Payments: Stripe Subscriptions

- Voice AI: ElevenLabs Conversational AI, Twilio

- Engagement Predictor ML: Python, scikit-learn, XGBoost on a data pipeline from X API v2 and a base dataset from Kaggle.

- Chrome Extension: Same as Frontend and Chrome Extensions API

- Blog: Jekyll

- Infrastructure: Deployed on AWS Fargate using AWS Copilot for orchestration (ECS).

I'm building solo and just got the first trial user after 87 days of building in public. It's a long road but the feedback so far is encouraging.

[0] https://www.kaggle.com/code/shpatrickguo/tweet-virality-pred...