X-Talk: On the Underestimated Potential of Modular Speech-to-Speech Dialogue System

TL;DR

X-Talk introduces a modular speech-to-speech system framework that achieves low latency and high flexibility by combining specialized components with large language models, challenging the end-to-end paradigm.

Contribution

The paper presents a decoupled, modular framework for speech-to-speech systems that maintains low latency and flexibility, demonstrating the potential of cascaded pipelines over end-to-end models.

Findings

Achieves sub-second latency with modular design

Integrates diverse front-end and understanding components

Revitalizes cascaded approach for speech systems

Abstract

We present X-Talk, an open-source framework that champions a decoupled, modular design for LLM-driven speech-to-speech (S2S) systems. While the dominant trend favors end-to-end (E2E) modeling to optimize information flow, these "omni-models" often struggle to balance the competing objectives of complex speech tasks within a single network. X-Talk challenges this paradigm by demonstrating that a systematically optimized cascaded pipeline can achieve sub-second latency without sacrificing modular flexibility. Our framework seamlessly integrates specialized front-end components (e.g., VAD, speech enhancement) and diverse understanding models (e.g., ASR, emotion, and environmental sound analysis) with LLM capabilities like retrieval-augmented generation (RAG) and tool use. By revitalizing the cascaded approach, X-Talk highlights the underestimated potential of modular S2S systems and provides a robust foundation for future research and applications.