06 · 2023–

Neural codec language models

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.

On this plate

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.

Microsoft2023

VALL-E

Codec LMresearchcloneemotionvendor demo

Zero-shot cloning as in-context learning.

Suno2023

Bark

Codec LMopencloneemotionvendor demo

[laughs] as a first-class output, not a failure mode.

SparkAudio2025

Spark-TTS

Codec LMopencloneemotionvendor demo

Open codec-LM TTS without a 7B backbone.

Canopy Labs2025

Orpheus

Codec LMopenclonestreamemotionno clip

LLM-backbone TTS with a permissive license.

PlateOfficial
Alibaba Qwen2025

Qwen3-TTS

Codec LMopenclonestreamemotionno clip

The open all-rounder a lot of 2026 local agents actually use.

PlateOfficial

All approaches

Kokoro 82M · af_heart