Voice agent architectures explained: STT→LLM→TTS vs. speech-to-speech vs. one API

Voice agent architectures can be divided into three main types, each with distinct trade-offs concerning latency, control, cost, and accuracy: the cascading STT→LLM→TTS pipeline, the single speech-to-speech model, and the unified voice agent API. The cascading pipeline offers the highest control and granularity by allowing the choice of best-in-class models for each stage, but it requires integration and coordination of three separate components, resulting in greater complexity and potential latency issues. The speech-to-speech model simplifies the architecture by processing audio input to output within a single model, reducing integration complexity but sacrificing control and transparency over individual stages. The unified voice agent API, such as AssemblyAI's offering, combines the benefits of both by running the full pipeline behind a single connection, offering a balance of control and simplicity, and is particularly suitable for production-grade accuracy without the need to integrate multiple vendors. A critical factor across all architectures is the accuracy of the speech-to-text (STT) layer, as any errors in transcription can propagate through the system, affecting the overall performance and reliability of the voice agent.

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