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🏆 Overall Model Ranking composite = BLEU 35% + quality 40% + speed 25%
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📋 Recent Samples
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Source lang:
Accepted/corrected eval decides quality. Shadow drift measures disagreement, not truth.
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✅ Accepted Eval Accuracy against verified/corrected transcript pairs
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🧪 Shadow Drift provider output vs current primary transcript
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🏷️ Live Routing Badges recent voice rows
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🔍 Recent Shadow Samples redacted comparison cards
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Target lang:
Source lang:
📈 Translation Quality by Model higher = better
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View by:
Which model is best per language?
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Model A:
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🔍 Samples — click a row to expand translations
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🔍 Cleanup Pass Breakdown why was the 2nd pass skipped or run?
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📝 By Language avg length, bullets, improvement per language
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Recent Entries
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Status:
Language:
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🎯 Production Transcription Quality live message quality_score rows
Scores here come from Retena production message heuristics. Use ASR Models → Accepted Eval for provider accuracy against verified/corrected transcript pairs.
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📐 How Production Quality Scoring Works
Each production transcription is scored 0–100 using fast heuristics (no LLM). The score reflects how likely the transcript is accurate and natural.
✅ Positive Signals
• +10 Word count ≥ 5
• +10 Avg word length 3–10 chars
• +5 Has punctuation
• +5 No looping patterns
• +10 Realistic speech rate (0.3–3.0 sec/word)
• +10 Avg word length 3–10 chars
• +5 Has punctuation
• +5 No looping patterns
• +10 Realistic speech rate (0.3–3.0 sec/word)
❌ Negative Signals
• −20 Word count < 3
• −15 Avg word length < 2 or > 15
• −20 Repeated substrings (hallucination)
• −30 Contains [BLANK_AUDIO] / [INAUDIBLE]
• −15 Impossibly fast (< 0.1 sec/word)
• −10 Impossibly slow (> 10 sec/word)
• −15 Avg word length < 2 or > 15
• −20 Repeated substrings (hallucination)
• −30 Contains [BLANK_AUDIO] / [INAUDIBLE]
• −15 Impossibly fast (< 0.1 sec/word)
• −10 Impossibly slow (> 10 sec/word)
80–100 Excellent
60–79 Good
40–59 Review
0–39 Poor
Base score: 60 · Clamped 0–100 · Pure heuristics, no LLM cost
📊 Production Quality by Language
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📋 Scored Production Messages
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