Results: add OmniVoice (4 systems)

README.md

@@ -104,7 +104,7 @@ breaks either direction fails CI.
 ### Does it actually work?
 
 The `vietnamese` subset is the control: no digits, acronyms or English, so there
-is nothing for the reference expansion to do. Measured across three systems, the
+is nothing for the reference expansion to do. Measured across four systems, the
 three reference policies are **identical to four decimal places** on that
 subset — while `challenging` moves a lot. The expansion is targeted, not a
 blanket loosening.
@@ -277,36 +277,41 @@ that, the column is not reproducible between runs.
 
 ## Results
 
-ZeroTTS vs. the two public Vietnamese XTTS-v2 finetunes. 137/137 items, scored
-by `zerobench_eval` at every policy:
+Four systems, 137/137 items each, scored by `zerobench_eval`:
 
-| Model | WER strict | WER norm | **WER robust** | SSIM | UTMOS | Excess silence |
-|---|---|---|---|---|---|---|
-| **[ZeroTTS](https://huggingface.co/zeroweight-ai/ZeroTTS)** | **5.26%** | **2.96%** | **1.03%** | 0.936 | **2.91** | **0.029 s** |
-| [XTTS-v2-vietnamse](https://huggingface.co/thivux/XTTS-v2-vietnamse) | 18.83% | 17.82% | 16.42% | **0.940** | 2.43 | 0.532 s |
-| [viXTTS](https://huggingface.co/capleaf/viXTTS) | 20.22% | 19.47% | 18.40% | 0.935 | 2.35 | 0.233 s |
+| Model | WER (raw text) | WER (normalized) | SSIM | UTMOS | Excess silence |
+|---|---|---|---|---|---|
+| **[ZeroTTS](https://huggingface.co/zeroweight-ai/ZeroTTS)** | **1.03 %** | **0.56 %** | 0.936 | **2.91** | **0.029 s** |
+| [OmniVoice](https://huggingface.co/k2-fsa/OmniVoice) | 4.13 % | 2.12 % | **0.950** | 2.76 | 0.340 s |
+| [XTTS-v2-vietnamse](https://huggingface.co/thivux/XTTS-v2-vietnamse) | 16.42 % | 7.27 % | 0.940 | 2.43 | 0.532 s |
+| [viXTTS](https://huggingface.co/capleaf/viXTTS) | 18.40 % | 8.61 % | 0.935 | 2.35 | 0.233 s |
 
-The two baselines barely move between policies (18.83% → 16.42%) while ZeroTTS
-drops 5.1×. That asymmetry is informative: the baselines' errors are hallucinated
-and garbled speech, which no reference policy can excuse, whereas most of
-ZeroTTS's residual was formatting.
+**raw text** = the model reads `31/12/2025` and `ChatGPT` as written, the
+benchmark task. **normalized** = every model is handed the spoken-out form
+instead, simulating a perfect Vietnamese text frontend. Scoring references are
+identical in both, so the columns are comparable.
 
-**With a perfect text-normalization frontend.** Feeding every model the
-spoken-out `text_normalized` instead of raw orthography — an ablation, not a
-benchmark score — separates grapheme-to-spoken-form errors from acoustic ones:
+Per subset, raw text:
 
-| Model | raw text | pre-normalized text |
-|---|:-:|:-:|
-| **ZeroTTS** | **1.03%** | **0.56%** |
-| XTTS-v2-vietnamse | 16.42% | 7.27% |
-| viXTTS | 18.40% | 8.61% |
+| Subset | ZeroTTS | OmniVoice | XTTS-v2-vietnamse | viXTTS |
+|---|---|---|---|---|
+| `vietnamese` | **0.16 %** | 0.50 % | 7.92 % | 9.56 % |
+| `code_switch` | 0.97 % | **0.46 %** | 10.94 % | 9.25 % |
+| `cross_lingual` | **1.42 %** | 17.71 % | 21.37 % | 27.27 % |
+| `challenging` | **1.75 %** | 4.46 % | 27.86 % | 31.85 % |
 
-The baselines gain the most (their tokenizers have no Vietnamese number
-expansion) and still lose by 13–15×. Useful if you are deciding whether to
-invest in a text frontend or a better acoustic model.
+Worth reading the subsets, not just the total. OmniVoice leads on
+`code_switch` and on speaker similarity, and its overall figure is dominated by
+`cross_lingual` — foreign voice prompt, Vietnamese text — where it degrades by
+reference language (German 0.00 %, Korean 0.13 %, Japanese 0.41 %). The two
+XTTS finetunes gain the most from normalization because their tokenizers have
+no Vietnamese number expansion at all.
+
+OmniVoice was given its optional `language="vi"` hint, which its model card
+recommends; without it, it scores 5.15 % / 3.87 % instead.
 
 Full per-subset tables, per-item audits and reproduction commands live in the
-[ZeroTTS repository](https://github.com/zeroweight-ai/ZeroTTS/blob/main/evaluation/RESULTS.md).
+[ZeroTTS repository](https://github.com/zeroweight-ai/ZeroTTS/blob/main/docs/BENCHMARKS.md).
 
 **Submitting a result:** open a discussion on this dataset with your
 `summary.json` and a note on how the wavs were produced.