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🎙️ Identify and extract target speaker's speech from multi-speaker audio using deep learning, enhancing clarity in complex conversations.

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GITHUB · launched Oct 13, 2026 · 10 upvotes (top 95%)

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Could you build this?

Partial Wrapping pretrained target-speaker extraction models in a menu UI is doable with AI assistance, but good separation quality needs ML expertise, curated models, and GPU compute.

What it would actually take: The architecture is a Python backend around a speech separation model (such as SpeakerBeam-style or conditioned extraction networks) that takes a speaker enrollment sample and a mixed recording, with a UI on top. The hard part is achieving clean separation on real multi-speaker audio, which requires ML research or fine-tuning expertise, quality datasets, and GPU hardware for training or inference tuning.

Competitors

Other products that read as similar to this one : 806 launches clear the similarity bar, closest 8 shown.

Attention rank: #798 of 807 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 348 days after the earliest competitor.

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