# Samples

Six clips from `samples/`, synthesized by this model on the **Arm CPU alone**
(ONNX Runtime, 9 threads) on a DGX Spark GB10. No GPU involved, no cherry
picking — these are the first six sentences of the held-out evaluation set in
order, the same set the WER/CER numbers in [`EVAL.md`](EVAL.md) come from.

| file | text |
|---|---|
| `samples/sample_00.wav` | The weather changed suddenly this afternoon. |
| `samples/sample_01.wav` | Could you please pass me that book? |
| `samples/sample_02.wav` | Wow, I did not expect to see you here! |
| `samples/sample_03.wav` | Our meeting has been moved to three o'clock. |
| `samples/sample_04.wav` | She walked quietly across the empty room. |
| `samples/sample_05.wav` | How many people are coming to dinner tonight? |

24 kHz mono, 16-bit PCM.

**Listen before trusting any metric.** The word and character error rates in
`EVAL.md` measure whether an ASR model can recover the words. They say nothing
about naturalness, pacing or timbre. This model is a 3.76M-parameter vocoder
distilled from 3 hours of audio, and it sounds like it — the point is that it
is 4.8× smaller and 10× faster on an Arm CPU than the teacher, not that it
matches it.