Why I Built VoiceBridge: Taking Back Control of My Voice Workflow скачать в хорошем качестве

Why I Built VoiceBridge: Taking Back Control of My Voice Workflow

I spent months fighting with paid tools and janky workflows just to turn my voice into text and text back into audio. After enough frustration with SuperWhisper’s paywalls, Whispering’s broken clipboard support, and ElevenLabs subscriptions, I built VoiceBridge. It’s a free, local, cross-platform CLI that runs Whisper and VibeVoice on your own hardware with proper workflow integration. This is the story of why that mattered and how I built it. The Problem Started Simple Enough I was messing around with OpenAI’s Whisper model[¹] and VibeVoice on my PC one weekend. Both worked beautifully. Fast transcription, clean audio generation, all running locally on my RTX 5090. No cloud dependencies, no subscription fees, no privacy concerns. Just me and the models. Then I tried to use them for real work. That’s when things got messy. I wanted to dictate a quick email. Transcribe a podcast interview. Have my computer read back a draft I’d written. Basic stuff. The kind of workflow that should just work. On macOS, you hit a hotkey and dictate. Text appears under your cursor. Simple. But I wasn’t on macOS. And even if I was, the dictate function absolute sucks. So I went hunting for alternatives. The Great Tool Hunt (And Why It Sucked) First stop: SuperWhisper. Beautiful UI. Great reviews. Mac only. $20/month. Hard pass. Next up: Whispering for Windows. Finally, something that ran local models. I installed it, tested it, and immediately hit a wall. The “copy to clipboard” feature didn’t work. The “insert under cursor” feature? Also broken. I’d transcribe something and then have to manually copy-paste it like some kind of cave person. For text-to-speech, ElevenLabs was the gold standard. Incredible voice quality, simple API. Also $22/month for the starter plan. Also sending all my text to their servers. Here’s the thing: I have an RTX 5090 sitting in my case doing basically nothing when I’m writing. I can run Whisper[¹] and VibeVoice locally. I get privacy. I get speed. I get to feel smug about not paying monthly fees. But none of that matters if the tooling sucks. I didn’t want a fancy app. I wanted workflow integration. I wanted to: Hit a hotkey, talk, and have text appear under my cursor Copy text to my clipboard and have it read aloud Select a text file and generate an audio file from it Drag an audio file into a folder and get a transcript back The tools could do the AI part. None of them could do the workflow part. The Hacky Python Scripts Phase I’m an engineer. I solve problems. So I wrote some Python scripts. One script would listen to my microphone, run Whisper, and dump the result to a file. Another would read a file and pipe it to VibeVoice. A third would monitor a directory for new audio files and auto-transcribe them. It worked. Sort of. The problem was coordination. I’d be writing an email, want to dictate a sentence, switch to my terminal, run the script, wait for it to finish, copy the output, paste it into my email, and forget what I was going to say in the first place. Or I’d want to listen to an article while cooking. So I’d select the text, copy it to a file, run the script, wait for the audio to generate, open the audio file, and by then the pasta was overcooked. The individual pieces worked. The glue didn’t. I needed a real tool. Building VoiceBridge: The Plan I knew what I wanted. A single CLI that could: Run Whisper[¹] and VibeVoice locally Integrate with my actual workflow (hotkeys, clipboard, file monitoring) Work on Linux, Windows, and macOS Be extensible enough to swap models later The tech stack came together pretty fast. Python for the core. Typer[²] for the CLI. Pynput for global hotkeys. FFmpeg[³] for audio processing. The hard part wasn’t the AI. The AI was already solved. The hard part was making it not suck to use. Challenge 1: Hotkeys That Actually Work Let’s talk about global hotkeys for a second. On paper, it’s simple. Listen for a key combination, trigger a function. In practice, it’s a nightmare of OS-specific quirks. On Windows, you’ve got the Win32 API. On Linux, you’ve got X11 or Wayland (good luck). On macOS, you’ve got Accessibility permissions that users need to manually grant. I went with pynput because it abstracts most of that mess. But even then, there were gotchas. Some key combinations are reserved by the OS. Some only work when your app has focus. Some work differently depending on your desktop environment. The solution? Let users configure their own hotkeys. Don’t hardcode anything. Provide sane defaults, but make them overridable. And test on all three platforms. I set up a listener that runs in the background. When you hit the configured hotkey, it starts recording from your microphone. When you release it, it stops, runs Whisper, and either copies the result to your clipboard or inserts it under your cursor. That last part (insert under cursor) was the trickiest. On Li...