voice-agents

Build a voice agent using speech-to-speech architecture for direct audio-to-audio processing to achieve the lowest latency. This approach bypasses intermediate text steps, allowing real-time conversational AI interactions while overcoming background noise challenges.

Speech-to-speech architectures process direct audio-to-audio inputs for minimal latency, whereas pipeline architectures sequence STT, LLM, and TTS steps. Pipelines provide maximum control over each processing phase, while speech-to-speech prioritizes real-time response speed.

Detect when users start or stop speaking by implementing voice activity detection within your voice agent architecture. This capability ensures seamless turn-taking and natural conversation flow by accurately identifying speech boundaries in the audio stream.

Yes, implementing voice agents requires knowledge of AI and speech processing technologies. You need familiarity with text-to-speech, speech-to-text, and conversational AI concepts to effectively manage latency, background noise, and turn-taking capabilities.

Manage background noise and latency by utilizing pipeline architectures that sequence speech-to-text, LLM, and text-to-speech steps. This structured processing approach provides maximum control over each step to optimize audio quality and response times.

Choose a pipeline architecture over speech-to-speech when you need maximum control over each step in the STT, LLM, and TTS process. Pipelines allow granular optimization of text generation and speech synthesis rather than prioritizing raw audio latency.