Running Local AI Speech-to-Text in Browser CPU with WebAssembly: Zero Server Uploads

A developer built SolveMyMedia Transcribe, a browser-based speech-to-text tool that runs quantized Whisper models entirely on-device using WebAssembly SIMD and ONNX Runtime Web, so no audio is uploaded to a server. The tool decodes audio into 16kHz float buffers in browser memory and passes them to a local model runtime, with weights cached in IndexedDB after the first load, claiming zero API cost and full offline operation.

Beaming confidential client interviews, confidential board meetings, or unreleased podcast recordings to remote cloud speech-to-text APIs is a massive privacy risk. Every major "AI Transcription" startup asks you to upload your audio files to their cloud S3 buckets. Once uploaded, your voice data sits on remote servers subject to data leaks or model retraining. With modern WebAssembly SIMD and ONNX Runtime Web , we can execute quantized Whisper transformer models 100% locally inside your browser tab . That's why we created SolveMyMedia Transcribe https://solvemymedia.com/transcribe . Audio is decoded into 16kHz float buffers in browser memory and passed directly to the local model runtime: js import { pipeline } from '@xenova/transformers'; export async function transcribeLocalAudio audioBlob { // Model weights cached in IndexedDB after initial load const transcriber = await pipeline 'automatic-speech-recognition', 'Xenova/whisper-tiny.en', { device: 'webgpu' } ; const arrayBuffer = await audioBlob.arrayBuffer ; const output = await transcriber arrayBuffer, { chunk length s: 30, stride length s: 5 } ; return output.text; // 100% private, 0 bytes leave your machine } | Metric | Cloud Speech API OpenAI / Rev | SolveMyMedia Local AI Transcribe | |---|---|---| | Voice Privacy | Stored on external cloud servers | Air-gapped in client RAM | | API Costs | $0.006 per minute | $0.00 Unlimited | | Offline Support | ❌ Fails without internet | ✅ 100% Works in Airplane Mode | Test it out: 👉 Local AI Transcribe: https://solvemymedia.com/transcribe https://solvemymedia.com/transcribe Have you experimented with client-side AI inference in production? Let's discuss in the comments