Overview
Mobile phones have had audio input for a long time, but none of the default options are particularly satisfactory. And despite the rise of capable online AI-based transcription services, for very simple scenarios like "turn this recording into some text," there's still no easy tool.
OpenAI released Whisper in 2022, a powerful model capable of transcribing many languages - but even now, there's no straightforward way to use it without invoking the API directly.
The API
Under the hood, Whisper is a deep neural network trained end-to-end to map raw audio to text. Conceptually, you:
- Provide an audio input - the model analyzes the waveform to extract linguistic and acoustic features.
- Leverage learned representations - its multi-layer architecture handles background noise, varied accents, and low-quality recordings.
- Produce a transcription - Whisper outputs a sequence of text that you can display, store, or post-process.
This high-level interaction keeps things simple: feed in speech, get back text - no need to manage model internals or low-level signal processing.
The Utility
Today I'm sharing our free Transcriber tool, which I've been using for almost half a year. It does a solid job at what it's meant to do:
https://methodox.itch.io/transcriber
We likely won't have time to develop it further, but sharing it online makes it more accessible for others looking for a similar solution.
Challenges
Currently, there's a limit on audio length due to OpenAI API restrictions. It would also be ideal to add real-time transcription - something like Google Voice IME.
References