speaker-enrollment
Official implementation of similarity-based (ICPRAM 2025) and phoneme-based (PRICAI 2025) enrollment selection for speaker identification
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GITHUB · launched Oct 24, 2026 · 21 upvotes (top 57%)
- Horizontal
- Model & infra
- Developer
- AI-native
- Hobby / open-source project
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Partial The repository reimplements published research methods for enrollment selection, which is doable with vibe coding but needs ML knowledge and speaker datasets to validate results.
What it would actually take: Implement the similarity-based and phoneme-based selection algorithms from the two papers in PyTorch, using a speaker-recognition model such as ECAPA-TDNN as the embedding backbone. Phoneme-based selection also needs a forced aligner or phoneme recognizer. Reproducing the reported results needs labeled speech corpora (e.g., VoxCeleb or LibriSpeech), GPU compute, and a researcher who can interpret the methods.
Competitors
Other products that read as similar to this one : 711 launches clear the similarity bar, closest 8 shown.
Attention rank: #382 of 712 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).
Launched 359 days after the earliest competitor.
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