DuplexWorld: Can voice agents help you get through the day?
On the map: LLM agents and tool use → General LLM agent frameworks and benchmarks
Abstract (arXiv)
Speech-to-speech (S2S) voice agents are increasingly being incorporated into enterprise for customer care and as daily companions for consumers owing to the ease of the conversational modality over text. However, existing benchmarks fail to holistically evaluate voice agents along axes that really matter and are shaped as tests of agentic tool calling against a database. We believe they fail to adequately account for the diversity of conversational dialogue that mundane activities introduce and further, never test how faithfully an agent can assist on tasks that move beyond database manipulation. To tackle this DuplexWorld introduces six worlds where voice agents are especially useful: banking, insurance, travel, healthcare and logistics, and Pathfinding. Agents are evaluated on eleven different types of conversations across 156 scenarios (350+ hours of conversation), each testing conversational and analytical capability to varying degrees. Through extensive evaluation comprising agentic, conversational and speech-naturalness metrics, we show that even the best voice agents leave substantial room for improvement on all 3 axes (Pass@1: 0.490, turn-taking: 0.653, DNSMOS: 3.378). We perform extensive analysis on agentic v conversational performance, world- and conversation type-wise performance, failure modes exploring the explore v exploit lens for Pathfinding conversations and voice agent reliability over all six worlds.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Placed in General LLM agent frameworks and benchmarks, one of 16 directions in LLM agents and tool use. Builds on 15 of its 20 references that are in the map. First posted on arXiv 11 Aug 2026.
Builds on
15 of 20 references.
Closest ancestors · 4
Same direction, newest first
- 2026IHBench: Evaluating Post-Interruption Recovery in Voice Agents with Structured Workflows17 Jun
- 2026Full-Duplex-Bench-v3: Benchmarking Tool Use for Full-Duplex Voice Agents Under Real-World Disfluency6 Apr
- 2026τ-Voice: Benchmarking Full-Duplex Voice Agents on Real-World Domains14 Mar
- 2024τ-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains17 Jun
Other references · 11
- 2023SWE-bench: Can Language Models Resolve Real-World GitHub Issues?cited by 3,373
- 2021NISQA: A Deep CNN-Self-Attention Model for Multidimensional Speech Quality Prediction with Crowdsourced Datasetscited by 192
- 2021DNSMOS P.835: A Non-Intrusive Perceptual Objective Speech Quality Metric to Evaluate Noise Suppressorscited by 172
- 2025Full-Duplex-Bench: A Benchmark to Evaluate Full-duplex Spoken Dialogue Models on Turn-taking Capabilitiescited by 100
- 2025Full-Duplex-Bench v1.5: Evaluating Overlap Handling for Full-Duplex Speech Modelscited by 54
- 2025Talking Turns: Benchmarking Audio Foundation Models on Turn-Taking Dynamicscited by 47
- 2025Full-Duplex-Bench-v2: A Multi-Turn Evaluation Framework for Duplex Dialogue Systems with an Automated Examinercited by 41
- 2026Full-Duplex Interaction in Spoken Dialogue Systems: A Comprehensive Study from the ICASSP 2026 HumDial Challengecited by 13
- 2026A Survey of Full-Duplex Spoken Dialogue Systems: Architectural Hierarchy, Interaction Ontology, and Decision State Machinecited by 8
- 2026The ICASSP 2026 HumDial Challenge: Benchmarking Human-like Spoken Dialogue Systems in the LLM Eracited by 5
- 2026EchoChain: A Full-Duplex Benchmark for State-Update Reasoning Under Interruptionscited by 5
Built on by
Citing papers per year: 2026: 4.
4 papers.
- 2026DuplexSpeechBench-IFEval: Evaluating Implicit Instruction Following in Full-Duplex Voice Agentscited by 1
- 2026τ-Elicitation: Benchmarking multi-turn entity extraction in voice agentscited by 0
- 2026APEX-Voice: Can Voice Agents Complete Professional Workflows Through Full-Duplex Interactioncited by 0
- 2026Conversation Is a Two-Body Problem: Dyadic Evaluation of Full-Duplex Dialogue Modelscited by 0
- 2026Conversation Is a Two-Body Problem: Dyadic Evaluation of Full-Duplex Dialogue Models6 Oct 2026
- 2026APEX-Voice: Can Voice Agents Complete Professional Workflows Through Full-Duplex Interaction28 Sep 2026
- 2026τ-Elicitation: Benchmarking multi-turn entity extraction in voice agents11 Sep 2026
- 2026DuplexSpeechBench-IFEval: Evaluating Implicit Instruction Following in Full-Duplex Voice Agents3 Sep 2026
Similar, not cited
Close in wording, no citation either way
- 2026Evaluating Real-Time Voice Agents: From Component Quality to Grounded Outcomes
- 2026DuplexAgent-RSI: Recursive Harness Improvement for Full-Duplex Voice Agent Collaboration
- 2026Talk2Agent: Benchmarking Voice Interfaces for Text Agents
- 2025Cloning a Conversational Voice AI Agent from Call,Recording Datasets for Telesales
- 2023Dialogue Agents 101: A Beginner's Guide to Critical Ingredients for Designing Effective Conversational Systems
- 2025Everything Counts: The Managed Omnirelevance of Speech in Human-Voice Agent Interaction
- 2026Benchmarking LLM Judges for Voice-Agent Evaluation: Reliability, Calibration, and Human Oversight
- 2025A Desideratum for Conversational Agents: Capabilities, Challenges, and Future Directions