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PolyAI's Dialog-RSN-1 advances AI telephony by integrating speech recognition with turn-taking logic in a single request-based model, eliminating the latency and data loss inherent to traditional cascaded ASR-to-LLM stacks. By keeping text-to-speech separate from the audio-native processing layer, this architecture preserves voice control while achieving sub-300ms response times for enterprise call centers. This product represents a significant shift toward efficient, real-time multimodal interaction without requiring always-on GPU streams or sacrificing pronunciation flexibility.
PolyAI Releases Dialog-RSN-1: An Audio-Native Dialog Model That Fuses Turn-Taking, Speech Recognition, Function Calling, And Response
PolyAI has introduced Dialog-RSN-1, a dialog model that perceives caller audio directly instead of reading an ASR transcript. It fuses turn-taking, speech recognition, function calling, and response generation into a single audio-native model, keeps TTS separate so the output voice stays controllable, and runs as a request-based LLM rather than an always-on stream. PolyAI reports sub-300ms responses in live deployments. The post PolyAI Releases Dialog-RSN-1: An Audio-Native Dialog Model That Fuses Turn-Taking, Speech Recognition, Function Calling, And Response appeared first on MarkTechPost.
PolyAI has introduced Dialog-RSN-1, a dialog model that perceives the caller’s audio directly instead of reading a transcript. It fuses turn-taking, speech recognition, function calling and response generation into one audio-native model, and is already handling live production calls. Dialog-RSN-1 is audio-aware on the input side only; TTS stays separate, so the output voice remains controllable. It runs as a request-based LLM probed on demand, not an always-on stream that pins…
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