MULTI-Bench: A Multi-Turn Interactive Benchmark for Assessing Emotional Intelligence ability of Spoken Dialogue Models
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Abstract (arXiv)
Spoken Dialogue Models (SDMs) have advanced rapidly, yet their ability to sustain genuinely interactive multi-turn conversations remains underexplored, as most benchmarks focus on single-turn exchanges. We introduce Multi-Bench, the first benchmark explicitly designed to evaluate SDMs in multi-turn interactive dialogue with an emphasis on emotional intelligence. Multi-Bench employs a hierarchical structure with a basic track for emotion understanding and reasoning and an advanced track for emotion support and application. It comprises five carefully designed tasks and about 3.2K samples, ranging from emotion recognition to complex reasoning and interactive dialogue, supported by a reproducible evaluation framework. We evaluate six representative SDMs on eight subsets of Multi-Bench. Results show that while current SDMs achieve good performance on basic understanding tasks, they still have room for improvement in advanced multi-turn interactive dialogue and reasoning-related tasks, particularly in emotion awareness and application.
Key facts. Cited by 9 papers in the map (data through 7 Oct 2026). Builds on 22 of its 26 references that are in the map. First posted on arXiv 2 Nov 2025.
Builds on
22 of 26 references.
References · 22
- 2025DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learningcited by 6,146
- 2024GPT-4o System Cardcited by 4,467
- 2025Qwen2.5-Omni Technical Reportcited by 704
- 2024GLM-4-Voice: Towards Intelligent and Human-Like End-to-End Spoken Chatbotcited by 218
- 2024AIR-Bench: Benchmarking Large Audio-Language Models via Generative Comprehensioncited by 215
- 2025Kimi-Audio Technical Reportcited by 210
- 2024VoiceBench: Benchmarking LLM-Based Voice Assistantscited by 192
- 2025Step-Audio 2 Technical Reportcited by 101
- 2021PsyQA: A Chinese Dataset for Generating Long Counseling Text for Mental Health Supportcited by 92
- 2023SpokenWOZ: A Large-Scale Speech-Text Benchmark for Spoken Task-Oriented Dialogue Agentscited by 71
- 2024SD-Eval: A Benchmark Dataset for Spoken Dialogue Understanding Beyond Wordscited by 67
- 2024EmoBench: Evaluating the Emotional Intelligence of Large Language Modelscited by 53
10 more
- 2024Advancing Large Language Models to Capture Varied Speaking Styles and Respond Properly in Spoken Conversationscited by 45
- 2024Let's Go Real Talk: Spoken Dialogue Model for Face-to-Face Conversationcited by 40
- 2024PsyDT: Using LLMs to Construct the Digital Twin of Psychological Counselor with Personalized Counseling Style for Psychological Counselingcited by 37
- 2024Benchmarking Open-ended Audio Dialogue Understanding for Large Audio-Language Modelscited by 28
- 2025EmergentTTS-Eval: Evaluating TTS Models on Complex Prosodic, Expressiveness, and Linguistic Challenges Using Model-as-a-Judgecited by 24
- 2025NVSpeech: An Integrated and Scalable Pipeline for Human-Like Speech Modeling with Paralinguistic Vocalizationscited by 14
- 2025Does Your Voice Assistant Remember? Analyzing Conversational Context Recall and Utilization in Voice Interaction Modelscited by 9
- 2025C3: A Bilingual Benchmark for Spoken Dialogue Models Exploring Challenges in Complex Conversationscited by 9
- 2025SOVA-Bench: Benchmarking the Speech Conversation Ability for LLM-based Voice Assistantcited by 7
- 2025Step-Audio-AQAA: a Fully End-to-End Expressive Large Audio Language Modelcited by 7
Built on by
Citing papers per year: 2025: 2; 2026: 7.
9 papers.
- 2026The ICASSP 2026 HumDial Challenge: Benchmarking Human-like Spoken Dialogue Systems in the LLM Eracited by 5
- 2026Hear2Act: Benchmarking When Prosody Should Change What an Assistant Doescited by 2
- 2025HeartBench: Probing Core Dimensions of Anthropomorphic Intelligence in LLMscited by 1
- 2026SpeechEQ: Benchmarking Emotional Intelligence Quotient in Socially Aware Voice Conversational Modelscited by 1
- 2026Enjoy Your Talk: A Human-Centered Benchmark for Multi-Turn Dialogue with Decoupled User Simulation, Target Modeling, and Judgingcited by 1
- 2026Multi-turn Conversational AI from Text to Multimodal Interaction: Data, Models, Evaluation, and Open Challengescited by 1
- 2025Style Amnesia: Investigating Speaking Style Degradation and Mitigation in Multi-Turn Spoken Language Modelscited by 0
- 2026GrowLoop: Self-Evolving Conversation Evaluation Seeded by Humancited by 0
- 2026CallScreenBench: Benchmarking Small Language Models as Phone Secretariescited by 0
- 2026Hear2Act: Benchmarking When Prosody Should Change What an Assistant Does20 Aug 2026
- 2026Multi-turn Conversational AI from Text to Multimodal Interaction: Data, Models, Evaluation, and Open Challenges18 Aug 2026
- 2026CallScreenBench: Benchmarking Small Language Models as Phone Secretaries2 Aug 2026
- 2026Enjoy Your Talk: A Human-Centered Benchmark for Multi-Turn Dialogue with Decoupled User Simulation, Target Modeling, and Judging11 Jul 2026
- 2026SpeechEQ: Benchmarking Emotional Intelligence Quotient in Socially Aware Voice Conversational Models24 Jun 2026
- 2026GrowLoop: Self-Evolving Conversation Evaluation Seeded by Human26 May 2026
- 2026The ICASSP 2026 HumDial Challenge: Benchmarking Human-like Spoken Dialogue Systems in the LLM Era9 Jan 2026
- 2025Style Amnesia: Investigating Speaking Style Degradation and Mitigation in Multi-Turn Spoken Language Models29 Dec 2025
- 2025HeartBench: Probing Core Dimensions of Anthropomorphic Intelligence in LLMs26 Dec 2025