---
license: mit
language:
  - en
pipeline_tag: text-to-speech
tags:
  - piper
  - vits
  - text-to-speech
  - synaptics
  - torq
  - npu
---

# Piper TTS for Synaptics Torq (SL2619)

Piper (VITS) text-to-speech, voice `en_US-libritts_r-medium` (904 speakers,
22.05 kHz), **split across CPU and NPU** for the Synaptics SL2619 board.

The VITS graph is cut where the per-phoneme durations are ceiled and summed —
the point at which the output length becomes exact:

```
text --[espeak]--> phoneme ids --> [partA]  (CPU, onnxruntime)  --> z [1,192,F], g [1,512,1]
                                              z,g --> [partB]   (NPU, bf16 vmfb) --> audio [F*256]
```

partA holds 85% of the *nodes* (small shape/attention ops) but partB — the
HiFi-GAN vocoder — holds 82% of the *time* and is pure convolution, which is
what the NPU accelerates. Because partA yields the exact frame count `F`, the
correct static vocoder window is known before the vocoder runs.

Measured on the SL2619 board: **2.2× real time** end to end, versus 1.0× for the
same model run entirely on the CPU. The bf16 NPU vocoder matches the fp32 CPU
vocoder at **39.6 dB SNR** (correlation 0.99998).

## Contents

| path | what it is |
|---|---|
| `onnx/partA.onnx` | Text encoder + duration predictor. Runs on the CPU under onnxruntime. |
| `onnx/partB_static_{1,2,4,6,8}s.bf16io.onnx` | The vocoder, statically shaped per window, bf16 I/O — the source the VMFBs were compiled from. |
| `onnx/en_US-libritts_r-medium.onnx` | The original monolithic Piper voice, for reference. |
| `vmfb/partB_static_{1,2,4,6,8}s.vmfb` | The vocoder compiled for the Torq NPU (NSS-only, bf16), one per window. |
| `tflite/partB_static_4s.{int8,int16x8}.tflite` | Quantized vocoder conversions (int8 was slower than bf16 on this target; kept for reference). |
| `voice/en_US-libritts_r-medium.onnx.json` | Voice config, including the phoneme→id map. |
| `espeak/phonemizerd` | Small resident espeak-ng phonemizer daemon (aarch64) mirroring libpiper's phonemization. |
| `espeak/espeak-ng-data.tar.gz` | espeak-ng dictionaries the daemon needs. |

The vocoder ships as five separate VMFBs because the NPU model is statically
shaped; each covers 1, 2, 4, 6 or 8 seconds of audio. Per sentence you pick the
smallest window that fits, edge-pad the latent up to it, and trim the output back
to `F × 256` samples.

## Usage

These files are consumed by the `piper_tts` demo in
[synaptics-torq/torq-examples](https://github.com/synaptics-torq/torq-examples),
which writes a `.wav` and plays it on the board's speaker:

```sh
cd piper_tts
pip install -r requirements.txt
cd .. && python setup_demos.py piper_tts
cd piper_tts && python src/infer.py --text "Hello from the Synaptics board."
```

The demo reads each window's frame width from the VMFB signature rather than
hardcoding it, so recompiling with a different set of windows needs no code
change.

## Licensing

The Piper voice and models are MIT. `espeak/phonemizerd` links espeak-ng
(**GPLv3**) statically; its source ships with the demo at
`piper_tts/piper_core/phonemizerd.c` in torq-examples, with the build command in
its header comment.