inflectsynth

InflectSynth is the text/frontend layer for Inflect v2 synthesis: inflectg2p produces model-ready token IDs, while ONNXVoice owns the split ONNX Runtime sessions for Inflect Nano v2 and Inflect Micro v2.

The package has a flat layout (no src/) and dynamic Git-tag versioning through setuptools-scm.

Install

CPU:

python -m pip install "inflectsynth[cpu]"

CUDA or DirectML:

python -m pip install "inflectsynth[gpu]"
python -m pip install "inflectsynth[directml]"

Python

from inflectsynth import InflectVoice

with InflectVoice.from_pretrained("nano-v2", providers="cpu") as tts:
    result = tts.synthesize(
        "A small voice can still have something meaningful to say.",
        speed=1.0,
        variation=0.667,
        seed=7,
    )
    result.save_wav("sample.wav")

Use micro-v2 (or alias micro) for the larger v2 model.

The first managed run downloads exactly two revision-pinned upstream artifacts, duration.onnx and decode.onnx, and verifies both byte size and SHA-256 before opening.

Voice contract

The upstream Inflect v2 base releases each contain one fixed synthetic English voice. Accordingly:

tts.available_voices == ("default",)

voice="default" is the only supported runtime voice. There are no hidden style rows, speaker embeddings, or reference-audio voice cloning inputs in the published v2 ONNX ABI.

Controls

The public upstream ranges are preserved:

• speed: 0.5 to 2.0, default 1.0
• variation: 0.0 to 1.0, default 0.667
• seed: integer, default 0

A call processes one input through one frontend/runtime request. InflectSynth does not currently implement the official runner's long-text wrapper behavior: punctuation-aware chunking, per-chunk pauses/noise, concatenation, or edge fades.

Local graphs

from inflectsynth import InflectVoice

with InflectVoice.from_local(
    duration_path="duration.onnx",
    decode_path="decode.onnx",
    providers="cpu",
) as tts:
    result = tts.synthesize("Local inference.")

Voice-level calibration

InflectSynth ships measured BS.1770 static-gain calibration for both managed v2 models. Calibration is opt-in; the default mode remains off, so existing synthesis returns the raw model level.

from inflectsynth import InflectVoice, SynthesisConfig, VoiceLevelConfig

config = SynthesisConfig(
    voice_level=VoiceLevelConfig(mode="calibrated"),
)

with InflectVoice.from_pretrained("nano-v2", providers="cpu") as tts:
    result = tts.synthesize(
        "Use the packaged voice-level calibration.",
        config=config,
    )

The v0.1.0 calibration catalog contains:

• inflect:nano-v2:default: -0.0423775698 dB
• inflect:micro-v2:default: -0.3353773193 dB

Both records target -24.0 LUFS using the inflectsynth-prepared-speech-v1 corpus and nine measurements per model (three prepared-speech stimuli × three seeds). The applied gain and catalog revision are reported under result.metadata["voice_level"]. Local/unmanaged graphs do not receive a managed calibration identity automatically.

Catalog

Catalog discovery is delegated to ONNXVoice. Its Inflect adapter uses the authoritative inflect-onnx-bundles catalog source and cache; InflectSynth does not package a second model catalog. For sibling-repository testing or a separately updated catalog, pass catalog_url="../inflect-onnx-bundles/catalog/models.json" to InflectVoice.from_pretrained() or the corresponding discovery API. The authoritative catalog repo is intentionally not a Python package.

Runtime ownership

InflectSynth owns text preparation and calls inflectg2p to produce the model-ready token IDs. It passes those IDs and the speed, variation, and seed controls to ONNXVoice's registered Inflect adapter. ONNXVoice owns catalog resolution, pinned artifact integrity checks, provider/session configuration, and ONNX graph execution; InflectSynth does not open ONNX Runtime sessions directly.

Real-model release smoke

The real CPU integration smoke is excluded from normal unit runs and downloads model files only when explicitly enabled. Install the candidate ONNXVoice checkout/wheel and InflectSynth's CPU test dependencies, then run from this repository root:

python -m pip install -e "../onnxvoice[cpu]" -e ".[cpu,dev]"
env INFLECTSYNTH_RUN_REAL_MODEL_TESTS=1 python -m pytest -s -m "integration and network" tests/integration/test_inflect_real_models.py

The test runs both nano-v2 and micro-v2 through real InflectG2P and ONNXVoice CPU inference, checks output/seed behavior, and prints the resolved revision, artifact sizes and SHA-256 digests, and runtime/package versions. Run this gate against the candidate ONNXVoice build before release.

Dynamic versioning

Versions come from Git tags through setuptools-scm; source archives without Git metadata use 0.1.dev0. inflectsynth.__version__ reports the installed distribution version.

License

Apache-2.0. Inflect code and weights referenced by this project are published by Owen Song under Apache-2.0; model weights are downloaded from their official Hugging Face repositories and are not included in this source package.