Why it matters
The dominant architecture pattern for text-to-speech in 2026 looks a lot like an LLM — an autoregressive transformer generating sequences of tokens, one frame of audio at a time. Samuel Humeau from Mistral walks through why the field converged there, how neural audio codecs solve the information-density problem (audio
My takeaway: The dominant architecture pattern for text-to-speech in 2026 looks a lot like an LLM — an autoregressive transformer generating sequences of tokens, one frame of audio at a time. Samuel Humeau from Mistral walks through why the field converged there, how neural audio codecs solve the information-density problem (audio