DuplexGen framework generates synthetic dialogue speech with emergent timing

Researchers have introduced DuplexGen, a novel framework for generating synthetic dialogue speech that decouples content, timing, and acoustics. Unlike traditional methods that pre-script conversational timing, DuplexGen uses a large language model to generate a script, followed by two full-duplex conversational models that interact in real-time. This approach allows conversational timing to emerge organically while maintaining the scripted content. A high-fidelity text-to-speech model then renders the final audio without altering the emergent timing, resulting in more natural conversational dynamics. AI

IMPACT This framework could lead to more realistic synthetic voices for virtual assistants and conversational AI systems.

RANK_REASON The cluster contains an academic paper detailing a new method for synthetic speech generation. [lever_c_demoted from research: ic=1 ai=1.0]

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• DuplexGen
• patient--clinician conversational speech corpus
• Text-to-speech modeling

• paper
• other

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