Project AURIONAI Use-Cases Research & Innovation

Large-Scale Zero-Shot Text-to-Speech

Text-to-speech trained on tens of thousands of hours that speaks in an unseen voice from a few seconds of reference audio.

Tier Grades

feasible

Tier A: Frontier AI labs

feasible

Microsoft scaled TTS training to 60K hours for VALL-E.

feasible

Tier B: Indonesian AI labs

feasible

F5-TTS shows a public 100K hours dataset is enough, which an Indonesian lab can combine with local speech.

stretch

Tier C: Institution units such as ITB

stretch

Collecting tens of thousands of hours is a stretch for a unit, though fine-tuning released models such as F5-TTS is not.

feasible

Tier D: Organisations such as SEMAI (PoT, PoC, PoV)

feasible

Released models clone a voice from 3 seconds of audio, enough for a proof of concept with consented voices.

Where this comes from
Tiers: a) frontier AI labs, b) Indonesian AI labs, c) institution units such as ITB, d) organisations such as SEMAI delivering proof of technology, concept and value. Each rationale cites the anchors below.

Anchors

  • ComputeF5-TTS reaches an inference real-time factor of 0.15; VALL-E, F5-TTS and CosyVoice abstracts give no training compute.
  • DataVALL-E: 60K hours of English speech and a 3-second prompt; F5-TTS: a public 100K hours multilingual dataset.
  • Team size (proxy)Proxy only (author count of an exemplar paper, not a headcount): 13 authors on VALL-E; 8 on F5-TTS.
  • Time horizonMonths.
  • Shelf-life signalsVoice cloning restricted by law or platform policy, Open models matching commercial arena leaders
  • Pipeline roleTier A and open labs release zero-shot TTS; Tier B adds Indonesian data; Tier C evaluates naturalness; Tier D builds voice products with consented voices.
Where this comes from
Team size is a proxy (author counts of exemplar papers), not a headcount.

Who and What

Exemplars
Observed actors
Linked models
+29

Papers

Where this comes from
The papers to read first: where the direction began, its current best, and a survey when one exists.

Sources

  1. arxiv.org/abs/2301.02111 https://arxiv.org/abs/2301.02111
  2. arxiv.org/abs/2410.06885 https://arxiv.org/abs/2410.06885
  3. arxiv.org/abs/2407.05407 https://arxiv.org/abs/2407.05407

To cite this page: Project AURION, AI Use-Cases Research & Innovation, "Large-Scale Zero-Shot Text-to-Speech", https://aurion.semai.id/topics/zero-shot-voice-cloning-tts/, records of October 2026.