| --- |
| license: apache-2.0 |
| language: |
| - en |
| pipeline_tag: text-to-speech |
| tags: |
| - coreml |
| - tts |
| - vits |
| - apple-silicon |
| - ane |
| base_model: |
| - owensong/Inflect-Micro-v2 |
| - owensong/Inflect-Nano-v2 |
| --- |
| |
| # Inflect v2 CoreML (Micro + Nano) |
|
|
| Fixed-shape CoreML conversion of [Inflect-Micro-v2](https://huggingface.co/owensong/Inflect-Micro-v2) |
| (9.36M params) and [Inflect-Nano-v2](https://huggingface.co/owensong/Inflect-Nano-v2) (3.97M params) — |
| ultra-tiny VITS-family end-to-end English TTS, 24 kHz mono, fp16. |
|
|
| Converted by [FluidInference](https://huggingface.co/FluidInference) (mobius); |
| conversion pipeline, parity checks, and benchmark harness live in the |
| `models/tts/inflect-v2/coreml/` directory of the mobius repo. |
|
|
| ## Contents |
|
|
| ``` |
| micro/ 9.4M params, ~19 MB fp16 total per graph set |
| encoder.mlpackage tokens+mask -> m_p, logs_p, logw [t_text=512] |
| synthesizer_f{256,384,512,640,768,896,1024,2048}.mlpackage |
| z_p+mask -> waveform [bucket frames x 256 samples] |
| upstream_config.json |
| nano/ 4.0M params, ~8 MB fp16 per graph set (same layout) |
| symbols.json keithito-style symbol table (178 symbols, add_blank interspersal) |
| LICENSE Apache-2.0 (upstream) |
| ``` |
|
|
| ## Inference pipeline |
|
|
| Two deterministic models with everything stochastic or dynamically shaped on the host: |
|
|
| 1. espeak-ng `en-us` phonemization (with stress) → symbol ids → intersperse blanks (`pad_id=0`) → pad to 512. |
| 2. `encoder`: → `m_p`, `logs_p`, `logw`. |
| 3. Host: `w = ceil(exp(logw))/speed`; repeat-expand `m_p`/`logs_p` to `y_len` frames; |
| `z_p = m_p + randn * exp(logs_p) * noise_scale` (default 0.667). |
| 4. Pick the smallest synthesizer bucket ≥ `y_len`; zero-pad `z_p`, mask valid frames. |
| 5. `synthesizer`: reverse coupling flow + HiFiGAN → waveform; trim to `y_len * 256` samples. |
|
|
| Buckets are fixed-shape for ANE compatibility; at 128-frame granularity padding |
| overhead is within ~5% of exact-shape synthesis. |
|
|
| ## Benchmarks (M5 Pro, macOS 26.6, GPU, MiniMax-English 100 phrases) |
|
|
| | Variant | Synth p50 / p95 | Agg RTFx | WER* | CER* | |
| |---|---|---|---|---| |
| | Micro | 25.7 / 35.5 ms | 245× | 1.43% | 0.44% | |
| | Nano | 13.2 / 16.9 ms | 460× | 1.92% | 0.57% | |
|
|
| \* Parakeet TDT v3 roundtrip, same scoring path as the |
| [FluidAudio](https://github.com/FluidInference/FluidAudio) TTS benchmarks. |
| fp16 parity vs the PyTorch reference: audio correlation > 0.9999, predicted |
| durations bit-identical. |
|
|
| ## Notes |
|
|
| - ANE: the synthesizer's waveform-rate tensors exceed the ANE width limit |
| (W ≤ 65536) above the 256-frame bucket; f256 reaches 77% ANE residency, |
| larger buckets run on GPU (which is faster at every size on M-series). |
| - English only, one voice per variant, no cloning. Sample rate 24 kHz. |
| - Upstream weights and frontend: Apache-2.0, © the Inflect authors. This repo |
| redistributes converted weights under the same license. |
|
|
