Researchers have developed DG^VoiC, a novel voice clustering framework designed to aid in insurance fraud investigations by identifying repeated speakers across call-center audio recordings. This system anonymizes sensitive information, preprocesses speech, extracts speaker embeddings, and uses cosine similarity clustering to link voices. Evaluated on real call-center data, the framework demonstrated high accuracy in identifying speaker consistency, offering a valuable new signal for fraud detection. AI
IMPACT This framework could enhance fraud detection capabilities by leveraging voice biometrics for identity verification in call centers.
RANK_REASON The cluster contains a research paper detailing a new technical framework.
- DG^VoiC
- Muhammad Shakeel Akram
- alphaXiv
- arXiv
- CatalyzeX
- DagsHub
- FNOL
- Gotit.pub
- Hugging Face
- ScienceCast
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