# Endpointing Model Benchmark Report

**Model:** `/data/smart-turn-v3.0.onnx`

**Generated:** 2026-01-07 17:31:01 UTC

## Accuracy Results

**Total Samples:** 31,527

**Unique Languages:** 🇸🇦 Arabic, 🇧🇩 Bengali, 🇩🇰 Danish, 🇩🇪 German, 🇬🇧 🇺🇸 English, 🇫🇮 Finnish, 🇫🇷 French, 🇮🇳 Hindi, 🇮🇩 Indonesian, 🇮🇹 Italian, 🇯🇵 Japanese, 🇰🇷 Korean, 🇮🇳 Marathi, 🇳🇱 Dutch, 🇳🇴 Norwegian, 🇵🇱 Polish, 🇵🇹 Portuguese, 🇷🇺 Russian, 🇪🇸 Spanish, 🇹🇷 Turkish, 🇺🇦 Ukrainian, 🇻🇳 Vietnamese, 🇨🇳 Chinese

**Unique Datasets:** chirp3_1, chirp3_2, chirp3_3_short, human_5, human_convcollector_1, liva_1, midcentury_1, mundo_1, orpheus_endfiller_1, orpheus_grammar_1, orpheus_midfiller_1, rime_2

### Overall Performance

| Metric  | Sample Count | Accuracy (%) | Precision | Recall |    F1 | FPR (%) | FNR (%) |
| :------ | -----------: | -----------: | --------: | -----: | ----: | ------: | ------: |
| Overall |       31,527 |        88.97 |     0.858 |  0.933 | 0.894 |    7.70 |    3.33 |

### Performance by Language

| Language      | Sample Count | Accuracy (%) | Precision | Recall |    F1 | FPR (%) | FNR (%) |
| :------------ | -----------: | -----------: | --------: | -----: | ----: | ------: | ------: |
| 🇰🇷 Korean     |          889 |        95.39 |     0.947 |  0.962 | 0.954 |    2.70 |    1.91 |
| 🇹🇷 Turkish    |          966 |        95.34 |     0.927 |  0.983 | 0.954 |    3.83 |    0.83 |
| 🇩🇪 German     |        1,322 |        95.23 |     0.928 |  0.980 | 0.954 |    3.78 |    0.98 |
| 🇵🇹 Portuguese |        1,398 |        94.49 |     0.927 |  0.962 | 0.944 |    3.65 |    1.86 |
| 🇯🇵 Japanese   |          834 |        94.36 |     0.925 |  0.967 | 0.945 |    3.96 |    1.68 |
| 🇳🇱 Dutch      |        1,398 |        94.28 |     0.925 |  0.968 | 0.946 |    4.08 |    1.65 |
| 🇫🇷 French     |        1,252 |        94.25 |     0.945 |  0.942 | 0.944 |    2.80 |    2.96 |
| 🇮🇹 Italian    |          782 |        93.22 |     0.898 |  0.974 | 0.935 |    5.50 |    1.28 |
| 🇵🇱 Polish     |          974 |        93.02 |     0.904 |  0.955 | 0.929 |    4.83 |    2.16 |
| 🇷🇺 Russian    |        1,468 |        92.03 |     0.891 |  0.966 | 0.927 |    6.20 |    1.77 |
| 🇺🇦 Ukrainian  |          929 |        91.82 |     0.881 |  0.954 | 0.916 |    6.03 |    2.15 |
| 🇮🇩 Indonesian |          971 |        90.73 |     0.854 |  0.979 | 0.912 |    8.24 |    1.03 |
| 🇮🇳 Hindi      |        1,284 |        89.95 |     0.856 |  0.970 | 0.910 |    8.49 |    1.56 |
| 🇩🇰 Danish     |          779 |        89.73 |     0.841 |  0.982 | 0.906 |    9.37 |    0.90 |
| 🇳🇴 Norwegian  |        1,014 |        89.64 |     0.869 |  0.938 | 0.903 |    7.20 |    3.16 |
| 🇨🇳 Chinese    |          929 |        89.34 |     0.861 |  0.943 | 0.900 |    7.75 |    2.91 |
| 🇫🇮 Finnish    |        1,010 |        87.52 |     0.813 |  0.974 | 0.886 |   11.19 |    1.29 |
| 🇸🇦 Arabic     |          947 |        86.17 |     0.810 |  0.950 | 0.875 |   11.30 |    2.53 |
| 🇬🇧 🇺🇸 English |        7,820 |        85.49 |     0.836 |  0.876 | 0.855 |    8.41 |    6.10 |
| 🇪🇸 Spanish    |        1,783 |        84.46 |     0.848 |  0.831 | 0.839 |    7.29 |    8.24 |
| 🇮🇳 Marathi    |          774 |        81.01 |     0.751 |  0.936 | 0.834 |   15.76 |    3.23 |
| 🇻🇳 Vietnamese |        1,004 |        79.58 |     0.721 |  0.960 | 0.824 |   18.43 |    1.99 |
| 🇧🇩 Bengali    |        1,000 |        78.70 |     0.717 |  0.935 | 0.811 |   18.10 |    3.20 |

### Performance by Dataset

| Dataset               | Sample Count | Accuracy (%) | Precision | Recall |    F1 | FPR (%) | FNR (%) |
| :-------------------- | -----------: | -----------: | --------: | -----: | ----: | ------: | ------: |
| rime_2                |          394 |        95.94 |     0.981 |  0.922 | 0.951 |    0.76 |    3.30 |
| orpheus_endfiller_1   |          181 |        95.03 |     1.000 |  0.902 | 0.949 |    0.00 |    4.97 |
| human_5               |          402 |        94.03 |     0.948 |  0.916 | 0.931 |    2.24 |    3.73 |
| chirp3_1              |       16,254 |        92.84 |     0.903 |  0.961 | 0.931 |    5.19 |    1.96 |
| human_convcollector_1 |           90 |        91.11 |     0.895 |  0.895 | 0.895 |    4.44 |    4.44 |
| orpheus_midfiller_1   |          140 |        90.00 |     0.877 |  0.905 | 0.891 |    5.71 |    4.29 |
| orpheus_grammar_1     |          163 |        87.12 |     0.848 |  0.918 | 0.881 |    8.59 |    4.29 |
| chirp3_2              |        8,428 |        86.08 |     0.802 |  0.956 | 0.872 |   11.75 |    2.17 |
| liva_1                |        3,831 |        83.74 |     0.839 |  0.838 | 0.838 |    8.09 |    8.17 |
| midcentury_1          |        1,044 |        77.39 |     0.704 |  0.917 | 0.797 |   18.58 |    4.02 |
| chirp3_3_short        |          104 |        74.04 |     0.818 |  0.562 | 0.667 |    5.77 |   20.19 |
| mundo_1               |          496 |        67.34 |     0.741 |  0.524 | 0.614 |    9.07 |   23.59 |