Piper ONNX Timing Models
Modified Piper TTS models with exposed duration tensors for temporal alignment.
Model Outputs
Output Type Description audioFloat32Array Synthesized speech durationsFloat32Array Frame counts per token
Duration Format
Durations are expressed in audio frames. To convert to milliseconds:
duration_ms = duration_frames × (hop_size / sample_rate) × 1000Standard values:
hop_size: 256sample_rate: 22050 (medium models)
Token Structure
The durations array corresponds to a token sequence that includes structural markers:
ID Type Description 0 padding Inter-token transitions 1 BOS Beginning of sentence 2 EOS End of sentence 3 space Word boundary 4+ phoneme Speech sounds
The token sequence is typically longer than the input phoneme string due to inserted structural tokens.
Configuration
Each model includes a .onnx.json file containing:
phoneme_id_map: Symbol-to-ID mappingsaudio.sample_rate: Sample rate for duration conversion
Source
Important Notes on Model Selection
Every model that was based on Lessac was excluded because they're not commercially usable.
Every MLS (Multilingual LibriSpeech) model is skipped because they failed to produce short audio reliably in any language (just gibberish comes out if the sentence isn't long enough).
