VoxConvo – "X but it's only voice messages"
Hi HN, I saw this tweet: "Hear me out: X but it's only voice messages (with AI transcriptions)" - and couldn't stop thinking about it. So I built VoxConvo. Why this exists: AI-generated content is drowning social media. ChatGPT replies, bot threads, AI slop everywhere. When you hear someone's actual voice: their tone, hesitation, excitement - you know it's real. That authenticity is what we're losing. So I built a simple platform where voice is the ONLY option. The experience: Every post is voice + transcript with word-level timestamps: Read mode: Scan the transcript like normal text or…
In plain words
VoxConvo is a social platform where all posts are voice messages paired with AI transcriptions and word-level timestamps. Users can read transcripts like traditional text or listen with highlighted words that sync in real-time. The platform includes visual voice editing, allowing users to remove filler words or mistakes by clicking specific words in the transcript to delete corresponding audio segments. Designed for people seeking authentic communication, VoxConvo addresses AI-generated content saturation by requiring voice as the only posting format, preserving tone and emotion while maintaining readability.
written from the facts on this page · September 2026
From the sources
In the maker’s words, at launch
Hi HN, I saw this tweet: "Hear me out: X but it's only voice messages (with AI transcriptions)" - and couldn't stop thinking about it. So I built VoxConvo. Why this exists: AI-generated content is drowning social media. ChatGPT replies, bot threads, AI slop everywhere. When you hear someone's actual voice: their tone, hesitation, excitement - you know it's real. That authenticity is what we're losing. So I built a simple platform where voice is the ONLY option. The experience: Every post is voice + transcript with word-level timestamps: Read mode: Scan the transcript like normal text or listen mode: hit play and words highlight in real-time. You get the emotion of voice with the scannability of text. Key features: - Voice shorts - Real-time transcription - Visual voice editing - click a word in transcript deletes that audio segment to remove filler words, mistakes, pauses - Word-level timestamp sync - No LLM content generation Technical details: Backend running on Mac Mini M1: - TypeGraphQL + Apollo Server - MongoDB + Atlas Search (community mongo + mongot) - Redis pub/sub for GraphQL subscriptions - Docker containerization for ready to scale Transcription: - VOSK real time gigaspeech model eats about 7GB RAM - WebSocket streaming for real-time partial results - Word-level timestamp extraction plus punctuation model Storage: - Audio files are stored to AWS S3 - Everything else is local Why Mac Mini for MVP? Validation first, scaling later. Architecture is containerized and ready to migrate. But I'd rather prove demand on gigabit fiber than burn cloud budget.
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