A frontend-backend architecture for tool calls in full-duplex speech models

Ke Hu; Slyne Deng; Chen Chen; Elena Rastorgueva; Edresson Casanova; Punit Kumar; Dharmendra Choudhary; Nikhil Srihari; Ameya Sunil Mahabaleshwarkar; Viet Anh Trinh; Slim Essid; Oluwatobi Olabiyi; Zhehuai Chen

arXiv · 2609.19334

A frontend-backend architecture for tool calls in full-duplex speech models

Ke Hu·Slyne Deng·Chen Chen·Elena Rastorgueva·Edresson Casanova·Punit Kumar·Dharmendra Choudhary·Nikhil Srihari·Ameya Sunil Mahabaleshwarkar·Viet Anh Trinh·Slim Essid·Oluwatobi Olabiyi·Zhehuai Chen

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Abstract

Full-duplex speech-to-speech (S2S) models provide natural, low-latency conversational interaction and would benefit from the ability to use external tools and complete voice-agent tasks. We propose a frontend-backend architecture where a duplex speech-to-text frontend learns to emit a delegation token and forwards streaming ASR transcripts to a text-based backend LLM for tool calls. Tool-call results from the backend are injected back into the frontend through a lightweight prefill-and-repeat mechanism and then synthesized using streaming TTS to the user. Our approach largely preserves regular duplex turn-taking, interruption handling, and low-latency interaction as it requires minimal modifications to the frontend model. In a single-turn tool-call evaluation, our system achieves 92-97% tool-call recall, competitive tool-call prediction performance, and 81.2% accuracy in rejecting irrelevant calls. When equipped with a larger backend (e.g., Qwen3-235B-A22B), our system achieves competitive results on Full-Duplex-Bench-V3 compared to open and closed source models, and significantly outperforms GPT-realtime-mini and Qwen3-Omni-30B-A3B-Instruct on EVA-Bench. These results demonstrate that backend delegation is an effective and modular approach for combining natural duplex speech interaction with strong agentic tool-call capabilities.

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Ke Hu, Slyne Deng, Chen Chen, Elena Rastorgueva, Edresson Casanova, Punit Kumar, Dharmendra Choudhary, Nikhil Srihari, Ameya Sunil Mahabaleshwarkar, Viet Anh Trinh, Slim Essid, Oluwatobi Olabiyi, Zhehuai Chen. 2026-09-18. A frontend-backend architecture for tool calls in full-duplex speech models. https://arxiv.org/abs/2609.19334

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