full-duplex

OpenAI has launched GPT-Live-1, a full-duplex voice model for API that enables natural, bidirectional voice conversations for developers, reducing latency and improving turn-taking in voice agents.

The paper introduces DuplexSpeechBench-IFEval, a benchmark for evaluating implicit instruction following in full-duplex voice agents, with 1,038 test cases across eight roles and five protocols to assess real-time speech systems' adherence to explicit vs. persona-implied behaviors.

NVIDIA has launched Nemotron 3 VoiceChat, an AI model enabling real-time, full-duplex voice interactions that allow natural interruptions, available via a live demo as part of its open-source NeMo Speech framework.

NVIDIA released NemotronLabs VoiceChat 11B, an open end-to-end full-duplex speech model enabling real-time conversational AI with ~450ms turn-taking latency, barge-in, and live tool calling, the first open full-duplex model to support tool calling.

OpenAI describes how they built GPT-Live, a full-duplex realtime voice AI system that eliminates the turn detector, enabling natural continuous conversation. The article details architecture improvements in inference, context management, and media transport over six months.

M3-DuplexBench is a new multi-turn, multilingual, multidomain benchmark for evaluating full-duplex spoken dialogue systems, supporting English and Japanese across casual conversation and question answering domains.

Microsoft is testing a new native real-time voice model, MAI Realtime, in early access on its MAI Playground. The full-duplex system supports multiple languages, low latency, and configurable turn-taking, positioning it as a competitor to OpenAI's GPT Live and Sesame.

Introduces Instruct-FD, a benchmark for evaluating whether full-duplex speech systems can follow explicit turn-taking instructions. Results show the best model achieves only 64.4% adherence, highlighting a significant gap in instruction-following turn management.

OpenAI integrates GPT-Live's full-duplex voice control into Codex and ChatGPT desktop app, enabling hands-free agentic coding with multi-threaded task execution.

This paper evaluates the reliability of Gemini models as audio judges for scoring full-duplex voice agent conversations, finding that Gemini 2.5 Flash shows strong agreement with human raters on most dimensions, though model swaps require re-validation.

OpenAI announces GPT-Live, a new full-duplex voice model that enables more natural, real-time conversations by allowing simultaneous listening and speaking, with GPT-5.5 as the backend model.

OpenAI released new full-duplex voice models GPT-Live-1 and GPT-Live-1 mini for more natural live conversations, allowing simultaneous speaking and listening, with improvements in turn-taking and context handling, and replacing Advanced Voice Mode in ChatGPT.

This paper introduces Lychee-FD, a native end-to-end full-duplex spoken language model that mitigates modality interference through a hierarchical parameter separation strategy, achieving significant improvements in speech intelligence and interaction fluidity.

TurnNat is a likelihood-based framework for automatically evaluating turn-taking naturalness in dyadic spoken dialogue, using a causal turn-taking prediction model trained on natural conversations to measure timing atypicality via negative log-likelihood.

BayLing-Duplex is a native full-duplex speech language model that enables a single autoregressive LLM to manage turn-taking and interruptions without external VAD modules, achieving high success rates and improved response quality over prior models.

This paper identifies 'state inertia' in full-duplex spoken language models, where the model's internal predictive focus lags during user interruptions, and proposes a training-free activation steering method to improve interruption handling.

Kyutai Labs released a new paper on using reinforcement learning to post-train speech models (Moshi and PersonaPlex) for more human-like interaction, including when to respond, wait, or give listening cues.

An analysis of half-duplex vs full-duplex architecture in AI voice models, discussing key features like overlap, backchannels, and barge-in that make voice agents sound robotic.

Raon-Speech is a 9B-parameter speech language model for English and Korean, supporting understanding, answering, and generation, with a full-duplex extension Raon-SpeechChat for natural real-time conversation. It achieves strong performance across 42 benchmarks and is fully open-sourced.

This paper analyzes synchronization and turn-taking dynamics in full-duplex speech dialogue models by simulating conversations between two instances of the Moshi model, measuring representational alignment via CKA and predicting turn boundaries with LSTM probes.