So far you've been learning about text based AIs but voice AIs has ben advancing at a very rapid speed. But how do they work?
There are two main approaches: traditional pipeline systems and newer voice-to-voice models. Each has distinct advantages and limitations.
Engagement Message
Have you noticed delays when talking to voice assistants like Siri or Alexa?
Traditional voice AI uses a three-step pipeline: Speech-to-Text (STT), then Large Language Model processing, then Text-to-Speech (TTS).
Your voice → STT converts to text → LLM thinks and responds in text → TTS converts back to speech.
This sequential approach works but creates natural delays at each step.
Engagement Message
Why can this feel unnatural?
Voice-to-Voice (V2V) models take a different approach - they process speech directly without converting to text first.
Think of it like a human conversation: you hear speech, understand meaning, and respond with speech all in one fluid process.
Engagement Message
Which sounds more natural - translating everything through text or staying in speech throughout?
The biggest advantage of V2V is lower latency. Traditional pipelines add delays: STT processing time + LLM thinking time + TTS generation time.
V2V can respond much faster because it eliminates the text conversion steps. Some V2V systems respond in under 500 milliseconds.
Engagement Message
How important is response speed when you're having a natural conversation?
V2V models also preserve speech qualities like emotion, tone, pace, and accent that get lost in text conversion.
Traditional TTS often sounds robotic because it generates speech from plain text without emotional context from your original voice.
Engagement Message
Have you ever noticed how voice assistants respond in a flat, emotionless tone regardless of your mood?
