VALL-E
Zero-shot cloning as in-context learning.
06 · 2023–
Quantize speech into tokens with a neural codec. Then train a language model on those tokens, as if speech were text.
Playable examples
The VALL-E Bill Gates prompt clip is cloning as in-context learning. Bark’s README pizza clip is the other codec-LM habit: speech plus [laughs] from a text prompt.
VALL-E (Microsoft, 2023) made the claim sharp: take EnCodec-style discrete codes, train an autoregressive transformer on 60,000 hours, and cloning becomes in-context learning. Three seconds of a speaker are a prompt, not a fine-tune.
Bark (Suno) is the chaotic cousin: an audio LM that will also emit music, noise, and [laughs]. Fish Speech / Fish Audio S2 and Spark-TTS stay closer to TTS. Orpheus puts a Llama backbone behind the same idea. Qwen3-TTS is the 2026 open default in a lot of local stacks.
The failure modes change. Codec LMs hallucinate words, insert breaths in the wrong place, or lock onto the prompt’s room tone. They also copy emotion and acoustic environment in a way a vocoder stack never did. That is why this family and the spoken-dialogue models start to blur.
The VALL-E Bill Gates prompt clip is cloning as in-context learning. Bark’s README pizza clip is the other codec-LM habit: speech plus [laughs] from a text prompt.
Zero-shot cloning as in-context learning.
[laughs] as a first-class output, not a failure mode.
Open codec-LM TTS without a 7B backbone.
Top open-weight arena rank with a non-permissive license asterisk.
LLM-backbone TTS with a permissive license.
The open all-rounder a lot of 2026 local agents actually use.