Add disclosed utterance-level ASR robustness diagnostics
Browse files- README.md +3 -2
- evaluation/asr_robustness.json +928 -0
README.md
CHANGED
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@@ -67,8 +67,9 @@ The selected Inflect-Micro-v2 checkpoint scored **4.406 UTMOS22** and **1.23% se
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- All four systems synthesize the same 200 unseen English prompts.
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- Semantic WER uses Whisper-large-v3 and the disclosed English text normalizer.
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- UTMOS22 uses `tarepan/SpeechMOS` v1.2.0 with 5,000 paired bootstrap samples.
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- NISQA dimensions, signal diagnostics, categorized ASR failures, speaker consistency, and multi-seed robustness are under `evaluation/`.
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-
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</details>
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- All four systems synthesize the same 200 unseen English prompts.
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- Semantic WER uses Whisper-large-v3 and the disclosed English text normalizer.
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- UTMOS22 uses `tarepan/SpeechMOS` v1.2.0 with 5,000 paired bootstrap samples.
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+
- NISQA dimensions, signal diagnostics, categorized ASR failures, speaker consistency, and multi-seed robustness are under `evaluation/`.
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- `evaluation/asr_robustness.json` separates sentence failures, semantic character errors, tail WER, and category-level errors.
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- Competitor results apply only to the named checkpoints and voices, not every configuration of those projects.
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</details>
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evaluation/asr_robustness.json
ADDED
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@@ -0,0 +1,928 @@
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| 1 |
+
{
|
| 2 |
+
"format": "inflect_tts_asr_robustness_summary_v1",
|
| 3 |
+
"source_format": "inflect_tts_multi_asr_wer_v1",
|
| 4 |
+
"asr": "whisper-large-v3",
|
| 5 |
+
"notes": [
|
| 6 |
+
"Character error rate is calculated over semantic-normalized ASR transcripts.",
|
| 7 |
+
"Sentence error rate counts any utterance with at least one semantic word edit.",
|
| 8 |
+
"These metrics measure ASR recoverability and do not replace human listening."
|
| 9 |
+
],
|
| 10 |
+
"systems": {
|
| 11 |
+
"inflect-micro-v2-finalist": {
|
| 12 |
+
"overall": {
|
| 13 |
+
"utterances": 200,
|
| 14 |
+
"semantic_errors": 32,
|
| 15 |
+
"semantic_words": 2608,
|
| 16 |
+
"semantic_wer": 0.012269938650306749,
|
| 17 |
+
"failed_utterances": 21,
|
| 18 |
+
"sentence_error_rate": 0.105,
|
| 19 |
+
"exact_sentence_rate": 0.895,
|
| 20 |
+
"character_errors": 62,
|
| 21 |
+
"reference_characters": 13718,
|
| 22 |
+
"character_error_rate": 0.004519609272488701,
|
| 23 |
+
"mean_utterance_wer": 0.021512501387501385,
|
| 24 |
+
"p95_utterance_wer": 0.18181818181818182,
|
| 25 |
+
"worst_utterance_wer": 1.0
|
| 26 |
+
},
|
| 27 |
+
"categories": {
|
| 28 |
+
"conversational": {
|
| 29 |
+
"utterances": 25,
|
| 30 |
+
"semantic_errors": 0,
|
| 31 |
+
"semantic_words": 309,
|
| 32 |
+
"semantic_wer": 0.0,
|
| 33 |
+
"failed_utterances": 0,
|
| 34 |
+
"sentence_error_rate": 0.0,
|
| 35 |
+
"exact_sentence_rate": 1.0,
|
| 36 |
+
"character_errors": 0,
|
| 37 |
+
"reference_characters": 1501,
|
| 38 |
+
"character_error_rate": 0.0,
|
| 39 |
+
"mean_utterance_wer": 0.0,
|
| 40 |
+
"p95_utterance_wer": 0.0,
|
| 41 |
+
"worst_utterance_wer": 0.0
|
| 42 |
+
},
|
| 43 |
+
"descriptive": {
|
| 44 |
+
"utterances": 16,
|
| 45 |
+
"semantic_errors": 0,
|
| 46 |
+
"semantic_words": 226,
|
| 47 |
+
"semantic_wer": 0.0,
|
| 48 |
+
"failed_utterances": 0,
|
| 49 |
+
"sentence_error_rate": 0.0,
|
| 50 |
+
"exact_sentence_rate": 1.0,
|
| 51 |
+
"character_errors": 0,
|
| 52 |
+
"reference_characters": 1146,
|
| 53 |
+
"character_error_rate": 0.0,
|
| 54 |
+
"mean_utterance_wer": 0.0,
|
| 55 |
+
"p95_utterance_wer": 0.0,
|
| 56 |
+
"worst_utterance_wer": 0.0
|
| 57 |
+
},
|
| 58 |
+
"emotional": {
|
| 59 |
+
"utterances": 24,
|
| 60 |
+
"semantic_errors": 0,
|
| 61 |
+
"semantic_words": 329,
|
| 62 |
+
"semantic_wer": 0.0,
|
| 63 |
+
"failed_utterances": 0,
|
| 64 |
+
"sentence_error_rate": 0.0,
|
| 65 |
+
"exact_sentence_rate": 1.0,
|
| 66 |
+
"character_errors": 0,
|
| 67 |
+
"reference_characters": 1574,
|
| 68 |
+
"character_error_rate": 0.0,
|
| 69 |
+
"mean_utterance_wer": 0.0,
|
| 70 |
+
"p95_utterance_wer": 0.0,
|
| 71 |
+
"worst_utterance_wer": 0.0
|
| 72 |
+
},
|
| 73 |
+
"homographs": {
|
| 74 |
+
"utterances": 6,
|
| 75 |
+
"semantic_errors": 1,
|
| 76 |
+
"semantic_words": 70,
|
| 77 |
+
"semantic_wer": 0.014285714285714285,
|
| 78 |
+
"failed_utterances": 1,
|
| 79 |
+
"sentence_error_rate": 0.16666666666666666,
|
| 80 |
+
"exact_sentence_rate": 0.8333333333333334,
|
| 81 |
+
"character_errors": 1,
|
| 82 |
+
"reference_characters": 375,
|
| 83 |
+
"character_error_rate": 0.0026666666666666666,
|
| 84 |
+
"mean_utterance_wer": 0.016666666666666666,
|
| 85 |
+
"p95_utterance_wer": 0.07500000000000001,
|
| 86 |
+
"worst_utterance_wer": 0.1
|
| 87 |
+
},
|
| 88 |
+
"long": {
|
| 89 |
+
"utterances": 15,
|
| 90 |
+
"semantic_errors": 1,
|
| 91 |
+
"semantic_words": 432,
|
| 92 |
+
"semantic_wer": 0.0023148148148148147,
|
| 93 |
+
"failed_utterances": 1,
|
| 94 |
+
"sentence_error_rate": 0.06666666666666667,
|
| 95 |
+
"exact_sentence_rate": 0.9333333333333333,
|
| 96 |
+
"character_errors": 6,
|
| 97 |
+
"reference_characters": 2206,
|
| 98 |
+
"character_error_rate": 0.0027198549410698096,
|
| 99 |
+
"mean_utterance_wer": 0.0018518518518518517,
|
| 100 |
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"p95_utterance_wer": 0.008333333333333304,
|
| 101 |
+
"worst_utterance_wer": 0.027777777777777776
|
| 102 |
+
},
|
| 103 |
+
"long_range": {
|
| 104 |
+
"utterances": 6,
|
| 105 |
+
"semantic_errors": 0,
|
| 106 |
+
"semantic_words": 121,
|
| 107 |
+
"semantic_wer": 0.0,
|
| 108 |
+
"failed_utterances": 0,
|
| 109 |
+
"sentence_error_rate": 0.0,
|
| 110 |
+
"exact_sentence_rate": 1.0,
|
| 111 |
+
"character_errors": 0,
|
| 112 |
+
"reference_characters": 744,
|
| 113 |
+
"character_error_rate": 0.0,
|
| 114 |
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"mean_utterance_wer": 0.0,
|
| 115 |
+
"p95_utterance_wer": 0.0,
|
| 116 |
+
"worst_utterance_wer": 0.0
|
| 117 |
+
},
|
| 118 |
+
"names_places": {
|
| 119 |
+
"utterances": 6,
|
| 120 |
+
"semantic_errors": 4,
|
| 121 |
+
"semantic_words": 57,
|
| 122 |
+
"semantic_wer": 0.07017543859649122,
|
| 123 |
+
"failed_utterances": 3,
|
| 124 |
+
"sentence_error_rate": 0.5,
|
| 125 |
+
"exact_sentence_rate": 0.5,
|
| 126 |
+
"character_errors": 13,
|
| 127 |
+
"reference_characters": 397,
|
| 128 |
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"character_error_rate": 0.0327455919395466,
|
| 129 |
+
"mean_utterance_wer": 0.07407407407407407,
|
| 130 |
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"p95_utterance_wer": 0.19444444444444442,
|
| 131 |
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"worst_utterance_wer": 0.2222222222222222
|
| 132 |
+
},
|
| 133 |
+
"narrative": {
|
| 134 |
+
"utterances": 24,
|
| 135 |
+
"semantic_errors": 1,
|
| 136 |
+
"semantic_words": 352,
|
| 137 |
+
"semantic_wer": 0.002840909090909091,
|
| 138 |
+
"failed_utterances": 1,
|
| 139 |
+
"sentence_error_rate": 0.041666666666666664,
|
| 140 |
+
"exact_sentence_rate": 0.9583333333333334,
|
| 141 |
+
"character_errors": 1,
|
| 142 |
+
"reference_characters": 1762,
|
| 143 |
+
"character_error_rate": 0.0005675368898978433,
|
| 144 |
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"mean_utterance_wer": 0.002777777777777778,
|
| 145 |
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"p95_utterance_wer": 0.0,
|
| 146 |
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"worst_utterance_wer": 0.06666666666666667
|
| 147 |
+
},
|
| 148 |
+
"numbers": {
|
| 149 |
+
"utterances": 6,
|
| 150 |
+
"semantic_errors": 10,
|
| 151 |
+
"semantic_words": 64,
|
| 152 |
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"semantic_wer": 0.15625,
|
| 153 |
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"failed_utterances": 5,
|
| 154 |
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"sentence_error_rate": 0.8333333333333334,
|
| 155 |
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"exact_sentence_rate": 0.16666666666666663,
|
| 156 |
+
"character_errors": 18,
|
| 157 |
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"reference_characters": 322,
|
| 158 |
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"character_error_rate": 0.055900621118012424,
|
| 159 |
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"mean_utterance_wer": 0.17462121212121215,
|
| 160 |
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"p95_utterance_wer": 0.35625,
|
| 161 |
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"worst_utterance_wer": 0.375
|
| 162 |
+
},
|
| 163 |
+
"punctuation": {
|
| 164 |
+
"utterances": 6,
|
| 165 |
+
"semantic_errors": 0,
|
| 166 |
+
"semantic_words": 65,
|
| 167 |
+
"semantic_wer": 0.0,
|
| 168 |
+
"failed_utterances": 0,
|
| 169 |
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"sentence_error_rate": 0.0,
|
| 170 |
+
"exact_sentence_rate": 1.0,
|
| 171 |
+
"character_errors": 0,
|
| 172 |
+
"reference_characters": 402,
|
| 173 |
+
"character_error_rate": 0.0,
|
| 174 |
+
"mean_utterance_wer": 0.0,
|
| 175 |
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"p95_utterance_wer": 0.0,
|
| 176 |
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"worst_utterance_wer": 0.0
|
| 177 |
+
},
|
| 178 |
+
"question": {
|
| 179 |
+
"utterances": 15,
|
| 180 |
+
"semantic_errors": 0,
|
| 181 |
+
"semantic_words": 165,
|
| 182 |
+
"semantic_wer": 0.0,
|
| 183 |
+
"failed_utterances": 0,
|
| 184 |
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"sentence_error_rate": 0.0,
|
| 185 |
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"exact_sentence_rate": 1.0,
|
| 186 |
+
"character_errors": 0,
|
| 187 |
+
"reference_characters": 834,
|
| 188 |
+
"character_error_rate": 0.0,
|
| 189 |
+
"mean_utterance_wer": 0.0,
|
| 190 |
+
"p95_utterance_wer": 0.0,
|
| 191 |
+
"worst_utterance_wer": 0.0
|
| 192 |
+
},
|
| 193 |
+
"rare_words": {
|
| 194 |
+
"utterances": 6,
|
| 195 |
+
"semantic_errors": 3,
|
| 196 |
+
"semantic_words": 57,
|
| 197 |
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"semantic_wer": 0.05263157894736842,
|
| 198 |
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"failed_utterances": 2,
|
| 199 |
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"sentence_error_rate": 0.3333333333333333,
|
| 200 |
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"exact_sentence_rate": 0.6666666666666667,
|
| 201 |
+
"character_errors": 3,
|
| 202 |
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"reference_characters": 500,
|
| 203 |
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"character_error_rate": 0.006,
|
| 204 |
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"mean_utterance_wer": 0.046969696969696974,
|
| 205 |
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"p95_utterance_wer": 0.16136363636363635,
|
| 206 |
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"worst_utterance_wer": 0.18181818181818182
|
| 207 |
+
},
|
| 208 |
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"short": {
|
| 209 |
+
"utterances": 24,
|
| 210 |
+
"semantic_errors": 4,
|
| 211 |
+
"semantic_words": 105,
|
| 212 |
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"semantic_wer": 0.0380952380952381,
|
| 213 |
+
"failed_utterances": 4,
|
| 214 |
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"sentence_error_rate": 0.16666666666666666,
|
| 215 |
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"exact_sentence_rate": 0.8333333333333334,
|
| 216 |
+
"character_errors": 10,
|
| 217 |
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"reference_characters": 458,
|
| 218 |
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"character_error_rate": 0.021834061135371178,
|
| 219 |
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"mean_utterance_wer": 0.07083333333333333,
|
| 220 |
+
"p95_utterance_wer": 0.25,
|
| 221 |
+
"worst_utterance_wer": 1.0
|
| 222 |
+
},
|
| 223 |
+
"technical": {
|
| 224 |
+
"utterances": 21,
|
| 225 |
+
"semantic_errors": 8,
|
| 226 |
+
"semantic_words": 256,
|
| 227 |
+
"semantic_wer": 0.03125,
|
| 228 |
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"failed_utterances": 4,
|
| 229 |
+
"sentence_error_rate": 0.19047619047619047,
|
| 230 |
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"exact_sentence_rate": 0.8095238095238095,
|
| 231 |
+
"character_errors": 10,
|
| 232 |
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"reference_characters": 1497,
|
| 233 |
+
"character_error_rate": 0.006680026720106881,
|
| 234 |
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"mean_utterance_wer": 0.030193615907901622,
|
| 235 |
+
"p95_utterance_wer": 0.2,
|
| 236 |
+
"worst_utterance_wer": 0.2857142857142857
|
| 237 |
+
}
|
| 238 |
+
}
|
| 239 |
+
},
|
| 240 |
+
"inflect-nano-v2-finalist": {
|
| 241 |
+
"overall": {
|
| 242 |
+
"utterances": 200,
|
| 243 |
+
"semantic_errors": 40,
|
| 244 |
+
"semantic_words": 2608,
|
| 245 |
+
"semantic_wer": 0.015337423312883436,
|
| 246 |
+
"failed_utterances": 23,
|
| 247 |
+
"sentence_error_rate": 0.115,
|
| 248 |
+
"exact_sentence_rate": 0.885,
|
| 249 |
+
"character_errors": 102,
|
| 250 |
+
"reference_characters": 13718,
|
| 251 |
+
"character_error_rate": 0.007435486222481412,
|
| 252 |
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"mean_utterance_wer": 0.021362234987234986,
|
| 253 |
+
"p95_utterance_wer": 0.18272727272727243,
|
| 254 |
+
"worst_utterance_wer": 0.4
|
| 255 |
+
},
|
| 256 |
+
"categories": {
|
| 257 |
+
"conversational": {
|
| 258 |
+
"utterances": 25,
|
| 259 |
+
"semantic_errors": 1,
|
| 260 |
+
"semantic_words": 309,
|
| 261 |
+
"semantic_wer": 0.003236245954692557,
|
| 262 |
+
"failed_utterances": 1,
|
| 263 |
+
"sentence_error_rate": 0.04,
|
| 264 |
+
"exact_sentence_rate": 0.96,
|
| 265 |
+
"character_errors": 5,
|
| 266 |
+
"reference_characters": 1501,
|
| 267 |
+
"character_error_rate": 0.0033311125916055963,
|
| 268 |
+
"mean_utterance_wer": 0.0036363636363636364,
|
| 269 |
+
"p95_utterance_wer": 0.0,
|
| 270 |
+
"worst_utterance_wer": 0.09090909090909091
|
| 271 |
+
},
|
| 272 |
+
"descriptive": {
|
| 273 |
+
"utterances": 16,
|
| 274 |
+
"semantic_errors": 0,
|
| 275 |
+
"semantic_words": 226,
|
| 276 |
+
"semantic_wer": 0.0,
|
| 277 |
+
"failed_utterances": 0,
|
| 278 |
+
"sentence_error_rate": 0.0,
|
| 279 |
+
"exact_sentence_rate": 1.0,
|
| 280 |
+
"character_errors": 0,
|
| 281 |
+
"reference_characters": 1146,
|
| 282 |
+
"character_error_rate": 0.0,
|
| 283 |
+
"mean_utterance_wer": 0.0,
|
| 284 |
+
"p95_utterance_wer": 0.0,
|
| 285 |
+
"worst_utterance_wer": 0.0
|
| 286 |
+
},
|
| 287 |
+
"emotional": {
|
| 288 |
+
"utterances": 24,
|
| 289 |
+
"semantic_errors": 0,
|
| 290 |
+
"semantic_words": 329,
|
| 291 |
+
"semantic_wer": 0.0,
|
| 292 |
+
"failed_utterances": 0,
|
| 293 |
+
"sentence_error_rate": 0.0,
|
| 294 |
+
"exact_sentence_rate": 1.0,
|
| 295 |
+
"character_errors": 0,
|
| 296 |
+
"reference_characters": 1574,
|
| 297 |
+
"character_error_rate": 0.0,
|
| 298 |
+
"mean_utterance_wer": 0.0,
|
| 299 |
+
"p95_utterance_wer": 0.0,
|
| 300 |
+
"worst_utterance_wer": 0.0
|
| 301 |
+
},
|
| 302 |
+
"homographs": {
|
| 303 |
+
"utterances": 6,
|
| 304 |
+
"semantic_errors": 4,
|
| 305 |
+
"semantic_words": 70,
|
| 306 |
+
"semantic_wer": 0.05714285714285714,
|
| 307 |
+
"failed_utterances": 2,
|
| 308 |
+
"sentence_error_rate": 0.3333333333333333,
|
| 309 |
+
"exact_sentence_rate": 0.6666666666666667,
|
| 310 |
+
"character_errors": 10,
|
| 311 |
+
"reference_characters": 375,
|
| 312 |
+
"character_error_rate": 0.02666666666666667,
|
| 313 |
+
"mean_utterance_wer": 0.05000000000000001,
|
| 314 |
+
"p95_utterance_wer": 0.17500000000000002,
|
| 315 |
+
"worst_utterance_wer": 0.2
|
| 316 |
+
},
|
| 317 |
+
"long": {
|
| 318 |
+
"utterances": 15,
|
| 319 |
+
"semantic_errors": 2,
|
| 320 |
+
"semantic_words": 432,
|
| 321 |
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"semantic_wer": 0.004629629629629629,
|
| 322 |
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"failed_utterances": 1,
|
| 323 |
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"sentence_error_rate": 0.06666666666666667,
|
| 324 |
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