Run High-Quality Kokoro TTS Locally on CPU with Privacy
Local, CPU-Friendly, High-Quality TTS (Text-to-Speech) with Kokoro
I demonstrate how to generate realistic, multi-language speech using the lightweight Kokoro model entirely on your CPU, ensuring complete privacy. By leveraging a simple Docker container compatible with the OpenAI speech API, you can easily integrate this 82M parameter model into your workflow. Even older hardware handles the synthesis efficiently, making high-quality local Text-to-Speech accessible without needing a dedicated GPU.
If that ancient CPU can do the job just fine, you know that this is a highly capable TTS system.
- sudobash1
I have used Kokoro fairly extensively for an accessibility product. I have loved working with it (especially because I don't have an NVidia GPU like many TTS of similar quality require).
I particularly appreciate the fact that it lets you manually add IPA pronunciation guides. There have been some cases where an important word is a homograph and Kokoro assumed the wrong pronunciation.
The place where it falls a little short is in saying just a single word or two. Try having it say simply "six" and it almost always says something like "ah-six-ah". I found a way around that though. If you give it a longer sentence to say (eg "The word is: six") it will say it fine. The trick is that the Kokoro API gives you the timestamp of each word in the sentence. So you can have a Python script crop out just the word you care about. The intonation is a little flat this way, but is very reliable.
I asked about this on the discord, and was told that it is a limitation of the small parameter size. But in fairness to Kokoro, even eleven-labs' voices suffer from this occasionally.
- dmayle
Fun... This is something I actually care about...
I used to keep a version of whisperx around, because I think it's important to have not just transcription, but also timing and speaker identification (e.g. for subtitles)... It depends on pyannote, though, which has some wierd licensing (and is tougher to script the installs because of it), so I wanted to look at something that both had better transcription, and supported diarization (the speaker and timing). I decided on parakeet for the transcription with softformer (the diarization), but most of the available engines for it don't include softformer.
I coded up an OpenAI compatible server for parakeet-rs ( https://github.com/altunenes/parakeet-rs ) (which does support softformer) and I've been using it with OpenWhispr (a desktop app for transcription that handles all sorts of neat thing).
I'm doing CPU-only transcription (because I use my GPUs for other stuff and haven't gotten around to adding in the GPU-path), but it's incredibly empowering to be able to have local transcriptions at will.
- SambhavGupta
A couple months back I wrote a chrome extension that does this on any webpage, with simultaneous highlighting of the sentence being read. Skips both the container launching step and the copy pasting website contents step. Might be useful to anyone trying to use kokoro ergonomically.
https://chromewebstore.google.com/detail/local-reader-ai-on-...
- bronco21016
Love this model. I’m GPU poor and have had FOMO that I haven’t played with local models at all. About a month ago I setup Kokoro on my GTX1650 to do TTS for an article reader. A simple WebUI lets me paste a URL or a chunk of copy pasted text. Python cleans it up and sends to Kokoro for TTS and it’s then served via RSS for Apple Podcasts. Then for my morning drive I’ll catch up on articles or blog posts I’ve gathered.
At some point I’d like to play with separate voices and see if I could build something like NotebookLM for kind of like a radio morning show of news items I’ve gathered.
- karimf
This repo is a good starting point for comparing TTS models https://github.com/5uck1ess/tts-bench
Kokoro is a really good model, considered it’s released 1.5 years ago. It’s punching above its weight https://5uck1ess.github.io/tts-bench/scores.html