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Building on HF
Gjxv
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Gjusev
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Gjusev
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posted
an
update
about 11 hours ago
A transcript can read fine and still get your phone number wrong. So I stopped scoring words and started scoring slots. VoxEntity-EU is an open German/French benchmark: does a speech model capture a dictated name, phone number, email, date, address or reference code exactly? One wrong character fails the slot. Whisper large-v3-turbo 34.2% · Voxtral Mini 3B 37.1% · correct-text ceiling 90.8%. 240 items per model, 95% CIs in the report. Emails: 0 to 20%. My first extractor version produced a wrong headline: "ASR is the bottleneck." It was my parser. I retracted it in public commits and shipped what survived. Read with care: synthetic speech (Qwen3-TTS), simulated phone line, provisional. A second TTS scores 10 points higher, so both results are published. Dataset https://huggingface.co/datasets/Gjusev/voxentity-eu Demo https://huggingface.co/spaces/Gjusev/voxentity-eu-results Full record, retraction included https://github.com/Gjusev/voxentity-eu
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Gjusev/voxentity-eu-results
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Gjusev/voxentity-eu
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Gjusev/MK-SH-1
0.1B
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Updated
1 day ago
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3
Gjusev/laya-triage-banking77
Text Classification
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0.4B
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15 days ago
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2