Brindille

A French text-to-speech model with 93,734 parameters and one voice, Estelle, that runs entirely in the browser: text in, 22.05 kHz audio out, no server, no ONNX Runtime. The whole page, engine included, is 2.7 MB (1.9 MB compressed).

Try the demo · runs on Alkove, my open-source on-device speech engine


Parameters	93,734 (145 of them in the synthesizer)
Model file	`tts.alk`, 266 KB (decoder weights in int8, encoder in float32), for the Alkove engine only: no ONNX, no PyTorch weights
Output	22,050 Hz, mono
Vocoder	none: the network predicts pitch, voicing and spectral envelopes, a harmonic + noise synthesizer renders the waveform
Runtime	the Alkove inference engine, compiled to WebAssembly (342 KB, 100 KB brotli)
Speed	~75× real time in WebAssembly on one thread (Apple M1 Max, Node)
Language, voice	French, Estelle

Intelligibility and sound

On 49 held-out sentences, transcribed by Whisper large-v3-turbo:

	WER	CER	DNSMOS OVR
This model	9.6 %	3.5 %	2.73
Reference audio of the same sentences	7.2 %	2.7 %	3.01

Whisper's own errors on names and rare words weigh on both rows.

Use

import { Tts } from './tts.js'

const tts = await Tts.load('./')          // tts.wasm, model/tts.alk, model/lex.alk, model/fr.dict.bin, model/tts.params.bin, model/tts.json
const pcm = tts.speak('Bonjour à tous.')   // Float32Array, tts.sampleRate (22,050 Hz)

speak(text, speed) takes a speed factor (1 by default). Everything runs on the page's thread; a sentence of a few seconds takes tens of milliseconds.

Files

File
`tts.wasm`	the engine, the text frontend and the synthesizer
`tts.js`	loads the files above and exposes `speak`
`model/tts.alk`	the network, two plans (encoder, decoder)
`model/tts.params.bin`	synthesizer and frontend constants
`model/tts.json`	sample rate and symbol names (to show phonemes)
`model/fr.dict.bin`	pronunciations of 19,662 French words: the most frequent ones and those Lex gets wrong
`model/lex.alk`	Lex, which reads every other word

Limits

French only, one voice (Estelle), no voice cloning.
Numbers are read out (integers, decimals with a comma); abbreviations, acronyms and symbols are not expanded.
Names and foreign words go through Lex, which can miss.
Liaisons follow rules for the most common words only.
The sound is slightly buzzy and muffled compared with natural speech.

License

Apache-2.0: the model, the WebAssembly module, tts.js and the page. model/fr.dict.bin is derived from the French dictionary of the Montreal Forced Aligner and stays under CC BY 4.0. The full notices are in NOTICE.

Credits

Voice: Estelle, from Pocket TTS by Kyutai (CC BY 4.0); the Estelle recording is Kyutai's, released under CC0 (tts-voices).
Network and synthesizer architecture: AuroraTTS-100K by AuroraAI-Research (Apache-2.0).
Pronunciations: the French dictionary of the Montreal Forced Aligner (CC BY 4.0), and Lex (Apache-2.0).
Inference: the Alkove engine (Apache-2.0).

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brindille