ChipChat: Low-Latency Cascaded Conversational Agent in MLX

• URL: http://arxiv.org/abs/2509.00078v1
• Date: Tue, 26 Aug 2025 20:40:24 GMT
• Title: ChipChat: Low-Latency Cascaded Conversational Agent in MLX
• Authors: Tatiana Likhomanenko, Luke Carlson, Richard He Bai, Zijin Gu, Han Tran, Zakaria Aldeneh, Yizhe Zhang, Ruixiang Zhang, Huangjie Zheng, Navdeep Jaitly,
• Abstract summary: ChipChat is a novel low-latency CS that overcomes traditional bottlenecks through architectural innovations and streaming optimizations.<n>Our work shows that strategically redesigned CSs can overcome their historical latency limitations, offering a promising path forward for practical voice-based AI agents.
• Score: 34.30974874671028
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The emergence of large language models (LLMs) has transformed spoken dialog systems, yet the optimal architecture for real-time on-device voice agents remains an open question. While end-to-end approaches promise theoretical advantages, cascaded systems (CSs) continue to outperform them in language understanding tasks, despite being constrained by sequential processing latency. In this work, we introduce ChipChat, a novel low-latency CS that overcomes traditional bottlenecks through architectural innovations and streaming optimizations. Our system integrates streaming (a) conversational speech recognition with mixture-of-experts, (b) state-action augmented LLM, (c) text-to-speech synthesis, (d) neural vocoder, and (e) speaker modeling. Implemented using MLX, ChipChat achieves sub-second response latency on a Mac Studio without dedicated GPUs, while preserving user privacy through complete on-device processing. Our work shows that strategically redesigned CSs can overcome their historical latency limitations, offering a promising path forward for practical voice-based AI agents.

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