Kokoro TTS

Kokoro is a frontier TTS model for its size of 82 million parameters (text in/audio out). This JavaScript library allows the model to be run 100% locally in the browser thanks to 🤗 Transformers.js. Try it out using our online demo!

Usage

First, install the kokoro-js library from NPM using:

``bash
npm i kokoro-js
`

You can then generate speech as follows:

`js
import { KokoroTTS } from "kokoro-js";

const model_id = "onnx-community/Kokoro-82M-v1.0-ONNX";
const tts = await KokoroTTS.from_pretrained(model_id, {
dtype: "q8", // Options: "fp32", "fp16", "q8", "q4", "q4f16"
device: "wasm", // Options: "wasm", "webgpu" (web) or "cpu" (node). If using "webgpu", we recommend using dtype="fp32".
});

const text = "Life is like a box of chocolates. You never know what you're gonna get.";
const audio = await tts.generate(text, {
// Use tts.list_voices() to list all available voices
voice: "af_heart",
});
audio.save("audio.wav");
`

Or if you'd prefer to stream the output, you can do that with:

`js
import { KokoroTTS, TextSplitterStream } from "kokoro-js";

const model_id = "onnx-community/Kokoro-82M-v1.0-ONNX";
const tts = await KokoroTTS.from_pretrained(model_id, {
dtype: "fp32", // Options: "fp32", "fp16", "q8", "q4", "q4f16"
// device: "webgpu", // Options: "wasm", "webgpu" (web) or "cpu" (node).
});

// First, set up the stream
const splitter = new TextSplitterStream();
const stream = tts.stream(splitter);
(async () => {
let i = 0;
for await (const { text, phonemes, audio } of stream) {
console.log({ text, phonemes });
audio.save(audio-${i++}.wav);
}
})();

// Next, add text to the stream. Note that the text can be added at different times.
// For this example, let's pretend we're consuming text from an LLM, one word at a time.
const text = "Kokoro is an open-weight TTS model with 82 million parameters. Despite its lightweight architecture, it delivers comparable quality to larger models while being significantly faster and more cost-efficient. With Apache-licensed weights, Kokoro can be deployed anywhere from production environments to personal projects. It can even run 100% locally in your browser, powered by Transformers.js!";
const tokens = text.match(/\s*\S+/g);
for (const token of tokens) {
splitter.push(token);
await new Promise((resolve) => setTimeout(resolve, 10));
}

// Finally, close the stream to signal that no more text will be added.
splitter.close();

// Alternatively, if you'd like to keep the stream open, but flush any remaining text, you can use the flush method.
// splitter.flush();
``

Voices/Samples

> [!TIP]
> You can find samples for each of the voices in the model card on Hugging Face.

$3

| Name | Traits | Target Quality | Training Duration | Overall Grade |
| ------------ | ------ | -------------- | ----------------- | ------------- |
| af_heart | 🚺❤️ | | | A |
| af_alloy | 🚺 | B | MM minutes | C |
| af_aoede | 🚺 | B | H hours | C+ |
| af_bella | 🚺🔥 | A | HH hours | A- |
| af_jessica | 🚺 | C | MM minutes | D |
| af_kore | 🚺 | B | H hours | C+ |
| af_nicole | 🚺🎧 | B | HH hours | B- |
| af_nova | 🚺 | B | MM minutes | C |
| af_river | 🚺 | C | MM minutes | D |
| af_sarah | 🚺 | B | H hours | C+ |
| af_sky | 🚺 | B | _M minutes_ 🤏 | C- |
| am_adam | 🚹 | D | H hours | F+ |
| am_echo | 🚹 | C | MM minutes | D |
| am_eric | 🚹 | C | MM minutes | D |
| am_fenrir | 🚹 | B | H hours | C+ |
| am_liam | 🚹 | C | MM minutes | D |
| am_michael | 🚹 | B | H hours | C+ |
| am_onyx | 🚹 | C | MM minutes | D |
| am_puck | 🚹 | B | H hours | C+ |
| am_santa | 🚹 | C | _M minutes_ 🤏 | D- |

$3

| Name | Traits | Target Quality | Training Duration | Overall Grade |
| ----------- | ------ | -------------- | ----------------- | ------------- |
| bf_alice | 🚺 | C | MM minutes | D |
| bf_emma | 🚺 | B | HH hours | B- |
| bf_isabella | 🚺 | B | MM minutes | C |
| bf_lily | 🚺 | C | MM minutes | D |
| bm_daniel | 🚹 | C | MM minutes | D |
| bm_fable | 🚹 | B | MM minutes | C |
| bm_george | 🚹 | B | MM minutes | C |
| bm_lewis | 🚹 | C | H hours | D+ |