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E2 TTS

Fully non-autoregressive zero-shot TTS with flow-matching mel generation.

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About

E2 TTS (Embarrassingly Easy Text-to-Speech) is a zero-shot speech synthesis model published by Microsoft researchers in June 2024 and accepted to IEEE SLT 2024. It is fully non-autoregressive: text becomes a character sequence with filler tokens, and a flow-matching mel spectrogram generator trained on audio infilling produces the speech.

The design needs no duration model, grapheme-to-phoneme converter, or monotonic alignment search, yet matches or beats systems like Voicebox and NaturalSpeech 3 on speaker similarity and intelligibility with human-level naturalness.

The paper proposes inference-friendly variants for flexible input representations. No official weights were released, but the simplicity of the approach made it influential in the flow-matching TTS wave.

Specs

Context window

Pricing

Free quota

API access

Weights

Closed — API only

Released

June 26, 2024

Benchmarks

Provider-reported unless a source says otherwise. Benchmarks are marketing-adjacent by nature — treat them as directional.

Use cases

text-to-speechvoice-cloningzero-shot-synthesisspeech-research

Trust score — 6/10

/10 trustMetrics-checked

Scored 6/10 (metrics tier, metrics-v1). Evidence: Verified via vendor site/docs/GitHub and reputable coverage, wave 86; Trending score 62/100 from researcher assessment.

Sources