flockspeech

Tiny text to speech that runs on your own device. No GPU, no cloud and no PyTorch: just ONNX Runtime and numpy.

This first release ships Junco v0.1, one English (US) voice at 24 kHz.

pip install flockspeech
flockspeech "Hello! I'm Junco, and I run on your own computer." -o hello.wav --play

from flockspeech import Junco

tts = Junco()                          # loads in under a second
audio = tts("Hello there.")            # float32 numpy array, 24 kHz mono
tts.save("Hello there.", "hello.wav")

for chunk in tts.stream(long_text):    # sentence by sentence: the first audio arrives fast
    play(chunk)

Why it suits small devices

Speed was measured on typical one-sentence replies, vocoder included. Add steps=4 (CLI --steps 4) for 1.5× more speed with slightly rougher audio.

Quality

Quality was measured on 40 unseen LibriTTS-R sentences with UTMOS (a predictor of listener ratings from 1 to 5):

In our wider benchmark of 150 sentences, Junco scored a word error rate of 1.71% with Whisper. Real recordings of the same sentences scored 2.30%.

Options

The CLI also reads text from a file (-f story.txt) or from standard input (echo hi | flockspeech -).

Limits

• One voice, English (US) only, in a read-aloud style.
• No text normalisation yet. Write numbers, money and abbreviations out in words ("five dollars", not "$5"; "Doctor", not "Dr.").
• Long text is split into sentences, and very long sentences are split at commas.
• Platforms: macOS (Apple silicon and Intel), Linux (x86-64 and ARM64, which includes a 64-bit Raspberry Pi OS) and Windows, wherever onnxruntime and espeakng-loader have wheels.

How it works

1. espeak-ng turns the text into phonemes.
2. A transformer encoder and a duration predictor read the phonemes.
3. A flow-matching decoder draws a mel spectrogram in 8 guided steps.
4. The Vocos vocoder turns the spectrogram into sound.

The acoustic model has 11.4M parameters and was trained from scratch on LJ Speech.

Licence

The code and the Junco weights are Apache-2.0. The bundled Vocos vocoder weights are MIT (Charactr Inc.). Phonemes come from phonemizer and espeak-ng (through espeakng-loader). Both are GPL-3.0 and are installed as separate dependencies, not included in this package. See NOTICE.