Whisper Web
Free, browser-based speech-to-text transcription powered by OpenAI Whisper.
AI & Machine Learning·Productivity
About
Whisper Web is a browser-based speech recognition platform powered by OpenAI's Whisper AI model, designed to transcribe audio in 98+ languages. It enables users to convert speech to text directly within their web browser without requiring downloads, installations, or API keys.
The tool is built for developers, creators, and anyone needing fast and accurate transcriptions, offering multiple input methods including microphone input, file uploads, and URLs. In its free mode, processing happens entirely locally on the user's device using WebGPU and WebAssembly, ensuring complete privacy with zero data leaving the browser.
What sets Whisper Web apart is its dual approach offering both a private, offline-capable local processing free tier and an unlimited cloud-powered tier for larger files up to 10 hours and batch uploads. It supports automatic language detection and various export formats like TXT, SRT, VTT, and JSON.
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FounderPlaybooks.
What other founders did to grow.
2722 dispatches from hundreds of founders, pulled from the week's best podcasts.
this phrase pet rock project it's really meant to diminish the value of a simple project of something that has Niche appeal and is a little bit quirky maybe a little bit simplistic or confined but I believe it's perfectly fine for India hackers to build these particular tools
Discount the "pet rock project" critique — it's envy, not market signal
When salaried-developer crowds (Hacker News, Reddit) call your niche tool a "pet rock project," treat it as projection, not feedback. They're conditioned to measure value by company scale, and an indie hacker shipping a simple useful tool on their own terms threatens that frame. The right response is silence and continued shipping — the people paying you money are the only signal that matters, not the people who hate-comment on a launch post.
Apps that find solid secondary product market fit have almost triple the minutes with their daily active users and almost double the daily active user to monthly active user ratio... what Calm did really well is they were out to solve a set of user problems that have some common symptoms.
Secondary Product-Market Fit Nearly Triples DAU Minutes and Doubles DAU/MAU Ratio
Google's internal data shows apps that find a secondary use case — Calm expanding from meditation to sleep stories — see engagement metrics nearly double and triple. The insight is to think about the underlying user problem (poor sleep, anxiety) rather than the feature category (meditation app). Secondary PMF comes from solving adjacent symptoms of the same problem, not from bolting on unrelated features.
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