Show HN: Slave – local dictation and TTS for macOS (3k words free)(slave.bot)
slave.bot
Show HN: Slave – local dictation and TTS for macOS (3k words free)
https://www.slave.bot/
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Some implementation details, since getting this to work well was not trivial.
My goal was “press hotkey, start talking, see text within ~1–2 seconds” on an M2 MacBook Pro, and support multiple languages.
First attempts (cloud) – I tried Hugging Face real-time transcription. It worked but latency was all over the place and costs would not scale. – I tried OpenAI real-time transcription. Latency was better, but when there was background noise, it'd transcribe wrong things. Saw 200ms responses. I can bring that back if I can make it stable. – I briefly experimented with Gemini for transcribing and formatting multi-language text. Quality was not consistent enough compared to Whisper for Multi language.
Local experiments – I used FFmpeg + Whisper CLI in a bunch of ways: batching, buffering, trying to “stream” partial results out of Whisper to make it feel live. – I also tried a local Llama model to format the raw transcript into an email. On an M2 Pro this took ~2 seconds for short emails and got much slower for long text. It looked nice but the latency was not acceptable for everyday use.
Where I ended up (for now) – Current version sticks to FFmpeg + Whisper CLI locally, optimized for short chunks so you usually see text within about 1–2 seconds. – I dropped the heavy on-device LLM formatting and keep the formatting logic much simpler so it stays predictable and fast.
Next step is to re-introduce “smart” formatting and meeting notes, but only when I can do it without blowing up latency. Happy to dig deeper into any of these if people are curious.
My goal was “press hotkey, start talking, see text within ~1–2 seconds” on an M2 MacBook Pro, and support multiple languages.
First attempts (cloud) – I tried Hugging Face real-time transcription. It worked but latency was all over the place and costs would not scale. – I tried OpenAI real-time transcription. Latency was better, but when there was background noise, it'd transcribe wrong things. Saw 200ms responses. I can bring that back if I can make it stable. – I briefly experimented with Gemini for transcribing and formatting multi-language text. Quality was not consistent enough compared to Whisper for Multi language.
Local experiments – I used FFmpeg + Whisper CLI in a bunch of ways: batching, buffering, trying to “stream” partial results out of Whisper to make it feel live. – I also tried a local Llama model to format the raw transcript into an email. On an M2 Pro this took ~2 seconds for short emails and got much slower for long text. It looked nice but the latency was not acceptable for everyday use.
Where I ended up (for now) – Current version sticks to FFmpeg + Whisper CLI locally, optimized for short chunks so you usually see text within about 1–2 seconds. – I dropped the heavy on-device LLM formatting and keep the formatting logic much simpler so it stays predictable and fast.
Next step is to re-introduce “smart” formatting and meeting notes, but only when I can do it without blowing up latency. Happy to dig deeper into any of these if people are curious.
Dictate in most languages. Types into any app.
Listen back with local Piper TTS.
3,000 words free. Then $6.99/month.
Next: joins meetings, transcribes, writes short notes. Later: lightweight Obsidian-style notes built from your text.
Built on Whisper + Piper. Runs on your machine.
Feedback on UX, speed, and pricing is welcome.