How AI Learned to Speak — a Rudrite Research film | Rudrite Research

Rudrite Research released a 47-minute documentary explaining how modern text-to-speech works, from sound waves as numbers to neural audio codecs and talking LLMs. The film covers key milestones like WaveNet, Tacotron, VALL-E, and current systems, aiming to make TTS technology accessible to a broad audience.

How AI Learned to Speak A from-zero ramp through how modern text-to-speech actually works: a sound wave as numbers, the neural codec that turns audio into tokens, TTS as next-token prediction, all the way to today’s talking LLMs — built on the verified explainers behind it. 47 min · 27 chapters · Watch on YouTube ↗ https://www.youtube.com/watch?v=8W qiZqocwo Chapters - 0:00 — TTS as next-token prediction - 0:50 — Sound is just numbers - 2:47 — The mel spectrogram - 4:13 — From text to phonemes - 5:37 — The alignment problem - 6:12 — Before deep learning - 6:56 — WaveNet - 7:43 — Tacotron and attention - 9:46 — FastSpeech and the variance adaptor - 12:15 — Flow, diffusion, and VITS - 13:38 — Audio as tokens: VQ and RVQ - 15:51 — Neural audio codecs - 19:09 — VALL-E and the three-slot frame - 21:37 — A gallery of modern systems - 24:58 — How these models are trained - 28:42 — Post-training with GRPO - 29:41 — Inference and the latency problem - 31:29 — Making it fast - 33:48 — Controlling prosody, voice, and emotion - 36:13 — A decade in one sentence - 36:57 — Moshi and Whisper - 38:12 — How we evaluate TTS - 39:17 — The whole field on one map - 40:13 — Reading a 2026 paper - 41:02 — The gist - 41:53 — Bonus: FACodec, AudioLM, and Tortoise - 44:08 — Bonus: multilingual, safety, and beyond