FastDialogueSidon
Fast two-speaker dialogue separation: Triton and TensorRT backends for FastDialogueSidon
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GITHUB · launched Oct 26, 2026 · 15 upvotes (top 75%)
- Horizontal
- Model & infra
- Developer
- AI-native
- Hobby / open-source project
Similar launches
See all 1032 similar launches →Could you build this?
Partial Wrapping a Triton or TensorRT inference server around an existing separation model is doable with help from an AI assistant, but the separation quality depends on a research model and the TensorRT optimization requires ML engineering skill.
What it would actually take: The stack is a pretrained two-speaker source separation model exported to ONNX, optimized with TensorRT, and served behind NVIDIA Triton with a simple audio API. The hard parts are getting a good model, which requires research-grade training data and expertise, and tuning latency and throughput on GPUs. A solo builder can deploy an existing open model, but building the model itself needs ML research capability.
Competitors
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Attention rank: #758 of 1033 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).
Launched 361 days after the earliest competitor.
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