To create AI companions that feel genuinely interactive, speech generation must go beyond producing high-quality audio—
it must understand and adapt to context in real time. Traditional text-to-speech (TTS) models generate spoken output directly from text but lack the contextual awareness needed for natural conversations. Even though recent models produce highly human-like speech, they struggle with the one-to-many problem: there are countless valid ways to speak a sentence, but only some fit a given setting. Without additional context—including tone, rhythm, and history of the conversation—models lack the information to choose the best option.