mlsanityData to 14 Oct 2026

Voila: Voice-Language Foundation Models for Real-Time Autonomous Interaction and Voice Role-Play

arXiv 2505.02707 ↗First posted 5 May 2025cs.AI cs.CL cs.SDcited by 10

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Abstract (arXiv)

A voice AI agent that blends seamlessly into daily life would interact with humans in an autonomous, real-time, and emotionally expressive manner. Rather than merely reacting to commands, it would continuously listen, reason, and respond proactively, fostering fluid, dynamic, and emotionally resonant interactions. We introduce Voila, a family of large voice-language foundation models that make a step towards this vision. Voila moves beyond traditional pipeline systems by adopting a new end-to-end architecture that enables full-duplex, low-latency conversations while preserving rich vocal nuances such as tone, rhythm, and emotion. It achieves a response latency of just 195 milliseconds, surpassing the average human response time. Its hierarchical multi-scale Transformer integrates the reasoning capabilities of large language models (LLMs) with powerful acoustic modeling, enabling natural, persona-aware voice generation -- where users can simply write text instructions to define the speaker's identity, tone, and other characteristics. Moreover, Voila supports over one million pre-built voices and efficient customization of new ones from brief audio samples as short as 10 seconds. Beyond spoken dialogue, Voila is designed as a unified model for a wide range of voice-based applications, including automatic speech recognition (ASR), Text-to-Speech (TTS), and, with minimal adaptation, multilingual speech translation. Voila is fully open-sourced to support open research and accelerate progress toward next-generation human-machine interactions.

Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). Builds on 44 of its 62 references that are in the map. First posted on arXiv 5 May 2025.

Builds on

44 of 62 references.

References · 44

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32 more
  1. 2021SoundStream: An End-to-End Neural Audio Codeccited by 771
  2. 2023Neural Codec Language Models are Zero-Shot Text to Speech Synthesizerscited by 752
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  12. 2023Character-LLM: A Trainable Agent for Role-Playingcited by 339
  13. 2021YourTTS: Towards Zero-Shot Multi-Speaker TTS and Zero-Shot Voice Conversion for everyonecited by 278
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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 3; 2026: 7.

10 papers.

Similar, not cited

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  1. 2025VoiceAssistant-Eval: Benchmarking AI Assistants across Listening, Speaking, and Viewing
  2. 2026Qwen-Audio-3.1-Realtime: Towards Reliable Agentic Voice Interaction
  3. 2026τ-Voice: Benchmarking Full-Duplex Voice Agents on Real-World Domains
  4. 2023Voice2Action: Language Models as Agent for Efficient Real-Time Interaction in Virtual Reality
  5. 2026Evaluating Real-Time Voice Agents: From Component Quality to Grounded Outcomes
  6. 2025Thinking While Speaking: Inference-Time Knowledge Transfer for Responsive and Intelligent Conversational Voice Agents
  7. 2026SpeechGym: An Audio-Native Gym for Training Voice Agents via Reinforcement Learning
  8. 2025Spoken Conversational Agents with Large Language Models