KAME: Tandem Architecture for Enhancing Knowledge in Real-Time Speech-to-Speech Conversational AI

Sakana AI

Sakana AI introduced KAME, a speech-to-speech conversational AI system that combines a fast response model with an asynchronous backend LLM to enable real-time reasoning during conversation rather than before speaking. The architecture allows swapping different LLMs like GPT-4.1, Claude Opus, or Gemini 2.5 Flash without changing the frontend system. The paper was accepted at ICASSP 2026 and demonstrated that different models excel at different tasks, with Claude scoring higher on reasoning and GPT on humanities questions.