# PersonaPlex: Voice and Role Control for Full Duplex Conversational Speech Models

arXiv: https://arxiv.org/abs/2602.06053 · HTML: https://mlsanity.com/paper/2602.06053/

## Key facts

- Cited by 63 papers in the map (data through 14 Oct 2026).
- Builds on 23 of its 33 references that are in the map.
- First posted on arXiv 14 Jan 2026.

## Builds on (most cited first, 23 of 23)

- [Adam: A Method for Stochastic Optimization](https://mlsanity.com/paper/1412.6980/) (2014)
- [Qwen3 Technical Report](https://mlsanity.com/paper/2505.09388/) (2025)
- [WavLM: Large-Scale Self-Supervised Pre-Training for Full Stack Speech Processing](https://mlsanity.com/paper/2110.13900/) (2021)
- [gpt-oss-120b & gpt-oss-20b Model Card](https://mlsanity.com/paper/2508.10925/) (2025)
- [Qwen2.5-Omni Technical Report](https://mlsanity.com/paper/2503.20215/) (2025)
- [VoxCeleb: a large-scale speaker identification dataset](https://mlsanity.com/paper/1706.08612/) (2017)
- [MiniCPM: Unveiling the Potential of Small Language Models with Scalable Training Strategies](https://mlsanity.com/paper/2404.06395/) (2024)
- [LibriTTS: A Corpus Derived from LibriSpeech for Text-to-Speech](https://mlsanity.com/paper/1904.02882/) (2019)
- [Moshi: a speech-text foundation model for real-time dialogue](https://mlsanity.com/paper/2410.00037/) (2024)
- [GLM-4-Voice: Towards Intelligent and Human-Like End-to-End Spoken Chatbot](https://mlsanity.com/paper/2412.02612/) (2024)
- [Mini-Omni: Language Models Can Hear, Talk While Thinking in Streaming](https://mlsanity.com/paper/2408.16725/) (2024)
- [VoiceBench: Benchmarking LLM-Based Voice Assistants](https://mlsanity.com/paper/2410.17196/) (2024)
- [Freeze-Omni: A Smart and Low Latency Speech-to-speech Dialogue Model with Frozen LLM](https://mlsanity.com/paper/2411.00774/) (2024)
- [Mini-Omni2: Towards Open-source GPT-4o with Vision, Speech and Duplex Capabilities](https://mlsanity.com/paper/2410.11190/) (2024)
- [Full-Duplex-Bench: A Benchmark to Evaluate Full-duplex Spoken Dialogue Models on Turn-taking Capabilities](https://mlsanity.com/paper/2503.04721/) (2025)
- [Libriheavy: a 50,000 hours ASR corpus with punctuation casing and context](https://mlsanity.com/paper/2309.08105/) (2023)
- [LLaMA-Omni2: LLM-based Real-time Spoken Chatbot with Autoregressive Streaming Speech Synthesis](https://mlsanity.com/paper/2505.02625/) (2025)
- [Beyond Turn-Based Interfaces: Synchronous LLMs as Full-Duplex Dialogue Agents](https://mlsanity.com/paper/2409.15594/) (2024)
- [OmniFlatten: An End-to-end GPT Model for Seamless Voice Conversation](https://mlsanity.com/paper/2410.17799/) (2024)
- [SALM-Duplex: Efficient and Direct Duplex Modeling for Speech-to-Speech Language Model](https://mlsanity.com/paper/2505.15670/) (2025)
- [URO-Bench: Towards Comprehensive Evaluation for End-to-End Spoken Dialogue Models](https://mlsanity.com/paper/2502.17810/) (2025)
- [Streaming Sequence-to-Sequence Learning with Delayed Streams Modeling](https://mlsanity.com/paper/2509.08753/) (2025)
- [VoxEval: Benchmarking the Knowledge Understanding Capabilities of End-to-End Spoken Language Models](https://mlsanity.com/paper/2501.04962/) (2025)

## Built on by (most cited first, 30 of 63)

- [MoshiRAG: Asynchronous Knowledge Retrieval for Full-Duplex Speech Language Models](https://mlsanity.com/paper/2604.12928/) (2026)
- [Multi-Faceted Interactivity Alignment in Full-Duplex Speech Models](https://mlsanity.com/paper/2606.11167/) (2026)
- [DuplexCascade: Full-Duplex Speech-to-Speech Dialogue with VAD-Free Cascaded ASR-LLM-TTS Pipeline and Micro-Turn Optimization](https://mlsanity.com/paper/2603.09180/) (2026)
- [Raon-Speech Technical Report](https://mlsanity.com/paper/2605.23912/) (2026)
- [Instruct-FD: Can Your Full-Duplex Speech System Follow Turn-Taking Instructions?](https://mlsanity.com/paper/2607.20460/) (2026)
- [DualTurn: Learning Turn-Taking from Dual-Channel Generative Speech Pretraining](https://mlsanity.com/paper/2603.08216/) (2026)
- [Overcoming State Inertia in Full-Duplex Spoken Language Models via Activation Steering](https://mlsanity.com/paper/2606.11386/) (2026)
- [NemotronLabs VoiceChat: An Open Full-duplex Speech-to-Speech Model with Tool Calling Capabilities](https://mlsanity.com/paper/2609.21967/) (2026)
- [VoxServe: Streaming-Centric Serving System for Speech Language Models](https://mlsanity.com/paper/2602.00269/) (2026)
- [MM-tau-p2: Persona-Adaptive Prompting for Robust Multi-Modal Agent Evaluation in Dual-Control Settings](https://mlsanity.com/paper/2603.09643/) (2026)
- [ASPIRin: Action Space Projection for Interactivity-Optimized Reinforcement Learning in Full-Duplex Speech Language Models](https://mlsanity.com/paper/2604.10065/) (2026)
- [DuplexChat: Constructing Speaker-Separated Full-Duplex Dialogue Speech at Scale for Spoken Dialogue Language Modeling](https://mlsanity.com/paper/2607.04941/) (2026)
- [M3-DuplexBench: A Multi-Turn, Multilingual, Multidomain Benchmark for Full-Duplex Spoken Dialogue Models](https://mlsanity.com/paper/2607.29125/) (2026)
- [X2-Turn: Frame-Synchronous Dual-Head Modeling for Joint Streaming ASR and Turn State Prediction](https://mlsanity.com/paper/2608.10878/) (2026)
- [VoiceChat-TTS: A Low-Latency Continuous Speech Synthesis Model for Interactive Agents](https://mlsanity.com/paper/2608.13831/) (2026)
- [DyaPlex: Full-Duplex Speech-Motion Model for Dyadic Interaction](https://mlsanity.com/paper/2606.03874/) (2026)
- [Cocktail-Talker: Multi-Speaker Dialog Modeling in Noisy Social Environments with Turn Action GRPO](https://mlsanity.com/paper/2607.27756/) (2026)
- [MP-Bench: Evaluating Voice Agents as a Multiparty Conversation Participant](https://mlsanity.com/paper/2609.13076/) (2026)
- [A frontend-backend architecture for tool calls in full-duplex speech models](https://mlsanity.com/paper/2609.19334/) (2026)
- [SpokenUS: A Spoken User Simulator for Task-Oriented Dialogue](https://mlsanity.com/paper/2603.16783/) (2026)
- [TiCo: Time-Controllable Spoken Dialogue Model](https://mlsanity.com/paper/2603.22267/) (2026)
- [RelayS2S: A Dual-Path Speculative Generation for Real-Time Dialogue](https://mlsanity.com/paper/2603.23346/) (2026)
- [VideoFDB: Evaluating Full-Duplex Vision-Speech Capabilities in Conversational Agents](https://mlsanity.com/paper/2605.30256/) (2026)
- [PolySpeech-100: A Large-Scale Benchmark for Speech Understanding Across 100+ Languages and Dialects](https://mlsanity.com/paper/2606.01016/) (2026)
- [DuplexGen: Adaptive Synthesis of Human-AI Turn-Taking Dialogues](https://mlsanity.com/paper/2607.26178/) (2026)
- [Agentic-DuplexGen: Decoupling Content, Timing, and Acoustics for Synthetic Dialogue Speech](https://mlsanity.com/paper/2608.16053/) (2026)
- [DuplexSpeechBench-IFEval: Evaluating Implicit Instruction Following in Full-Duplex Voice Agents](https://mlsanity.com/paper/2609.03423/) (2026)
- [Noise Adaptive Streaming Audio-Visual Speech Token Enhancement for Robust Full-Duplex Spoken Dialogue Models](https://mlsanity.com/paper/2609.08390/) (2026)
- [RetroThinker: Enabling Retrospective Thinking in Speech LLMs](https://mlsanity.com/paper/2609.11864/) (2026)
- [DuplexDrama: A Synthesized Dialogue Dataset with Scenarios, Full-Duplex Behaviors, Expressive Speech, and Sound Events](https://mlsanity.com/paper/2609.12872/) (2026)

## Abstract (arXiv)

Recent advances in duplex speech models have enabled natural, low-latency speech-to-speech interactions. However, existing models are restricted to a fixed role and voice, limiting their ability to support structured, role-driven real-world applications and personalized interactions. In this work, we introduce PersonaPlex, a duplex conversational speech model that incorporates hybrid system prompts, combining role conditioning with text prompts and voice cloning with speech samples. PersonaPlex is trained on a large-scale synthetic dataset of paired prompts and user-agent conversations, generated with open-source large language models (LLM) and text-to-speech (TTS) models. To evaluate role conditioning in real-world settings, we extend the Full-Duplex-Bench benchmark beyond a single assistant role to multi-role customer service scenarios. Experiments show that PersonaPlex achieves strong role-conditioned behavior, voice-conditioned speech, and natural conversational responsiveness, surpassing state-of-the-art duplex speech models and hybrid large language model-based speech systems in role adherence, speaker similarity, latency, and naturalness.