Context Spanning: A Communication Framework for Full-Duplex Speech Models and External LLM Backends

arXiv:2609.33443 · cs.CL, cs.SD, eess.AS · Submitted 2026-09-27 · Read on arXiv

cs.CL, cs.SD, eess.AS

Submitted: 2026-09-27

Updated: 2026-09-27

Code: https://github.com/mindlogic-ai/ContextSpanning

Terminology

• Benchmark — 13× in this paper · explained in 2 episodes
• RAG — 6× in this paper · explained in 3 episodes
• Transformer — 5× in this paper · explained in 2 episodes
• Accuracy — 4× in this paper · explained in 1 episode
• Foundation Model — 4× in this paper · explained in 3 episodes
• Full-duplex interaction — 2× in this paper · explained in 2 episodes
• Ablation — 1× in this paper · explained in 1 episode
• Ablation study — 1× in this paper · explained in 1 episode
• Automatic Speech Recognition — 1× in this paper
• Automatic Speech Recognition (ASR) — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Causal Inference — 1× in this paper · explained in 4 episodes
• Distillation — 1× in this paper · explained in 2 episodes
• Embeddings — 1× in this paper · explained in 2 episodes
• Foundation Models — 1× in this paper · explained in 7 episodes
• Generalization — 1× in this paper · explained in 13 episodes
• Generative AI — 1× in this paper · explained in 2 episodes
• KV cache — 1× in this paper · explained in 3 episodes
• Latent Representation — 1× in this paper · explained in 2 episodes
• Latent Representations — 1× in this paper · explained in 3 episodes
• Latent Space — 1× in this paper · explained in 7 episodes
• Loss Function — 1× in this paper · explained in 2 episodes
• Multimodal Dataset — 1× in this paper · explained in 2 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Reinforcement Learning — 1× in this paper · explained in 4 episodes
• Retrieval Augmented Generation — 1× in this paper
• Tokenization — 1× in this paper · explained in 2 episodes
• Transfer Learning — 1× in this paper · explained in 10 episodes

Sources

• Moshi: a speech-text foundation model for real-time dialogue
• DuplexSLA: A Full-Duplex Spoken Language Model with Synchronized Speech, Language, and Action
• MCPToolBench++: A Large Scale AI Agent Model Context Protocol MCP Tool Use Benchmark
• Gemma: Open Models Based on Gemini Research and Technology
• Qwen3-ASR Technical Report
• Full-Duplex-Bench-v3: Benchmarking Tool Use for Full-Duplex Voice Agents Under Real-World Disfluency

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