WhisperLive VS whisper-writer

Everything runs locally, we use:

- WhisperLive for the transcription - https://github.com/collabora/WhisperLive

Check out WhisperLive: https://github.com/collabora/WhisperLive

If you're grappling with the slow march from cool tech demos to real-world language model apps, you might wanna check out WhisperLive. It's this rad open-source project that’s all about leveraging Whisper models for slick live transcription. Think real-time, on-the-fly translated captions for those global meetups. It's a neat example of practical, user-focused tech in action. Dive into the details on their GitHub page

https://github.com/collabora/WhisperLive

The is another one that uses huggingface's implementation, but I haven't tried it since my spec doesn't support flash-att2

Curious to see how this works? Check out our demo page - https://col.la/transcription to generate your own transcription, summary, and translation, or use our browser extension - https://github.com/collabora/WhisperLive to get live transcriptions.

I've also made six small apps completely coded by ChatGPT (with GitHub Copilot contributing a bit as well). Here are the two largest:

PlaylistGPT (https://github.com/savbell/playlist-gpt): A fun little web app that allows you to ask questions about your Spotify playlists and receive answers from Python code generated by OpenAI's models. I even added a feature where if the code written by GPT runs into errors, it can send the code and the error back to the model and ask it to fix it. It actually can debug itself quite often! One of the most impressive things for me was how it was able to model the UI after the Spotify app with little more than me asking it to do exactly that.

WhisperWriter (https://github.com/savbell/whisper-writer): A small speech-to-text app that uses OpenAI's Whisper API to auto-transcribe recordings from a user's microphone. It waits for a keyboard shortcut to be pressed, then records from the user's microphone until it detects a pause in their speech, and then types out the Whisper transcription to the active window. It only took me two hours to get a working prototype up and running, with additions such as graphic indicators taking a few more hours to implement.

I created the first for fun and the second to help me overcome a disability that impacts my ability to use a keyboard. I now use WhisperWriter literally every day (I'm even typing part of this comment with it), and I used it to prompt ChatGPT to write the code for a few additional personal projects that improve my quality-of-life in small ways. If people are interested, I may write up more about the prompting and pair programming process, since I definitely learned a lot as I worked through these, including some similar lessons to the article!

Personally, I am super excited about the possibilities these AI technologies open up for people like me, who may be facing small challenges that could be easily solved with a tiny app written in a few hours tailored specifically to their problem. I had been struggling to use my desktop computer because the Windows Dictation tool was very broken for me, but now I feel like I can use it to my full capacity again because I can type with WhisperWriter. Coding now takes a minimal amount of keyboard use thanks to these AI coding assistants -- and I am super grateful for that!