15 Datasets for Building a Production TTS Voice in 2026

A curated list of 15 text-to-speech training datasets for teams shipping production voice models in 2026 covering emotional, multi-speaker, audiobook-derived, non-Latin script, indigenous-language datasets and more.

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15 Datasets for Building a Production TTS Voice in 2026

Why dataset selection matters more than scale

There was a time when the entire conversation about text-to-speech could be reduced to a single question: how many hours of clean single-speaker audio do you have? The standard answer was twenty-four hours of LJSpeech-style read audio and from that you got a model that sounded acceptable but flat.

That era is over. The teams shipping production TTS now have moved past "more hours of one speaker." They train on deliberate mixtures: emotional speech for prosody, multi-speaker corpora for speaker generalisation, audiobook-derived data for narrative style, dialect-specific data for regional authenticity, non-Latin script data for under-represented writing systems, indigenous-language data for cultural inclusion. The model's quality is the mixture's quality, and the mixture's quality is a function of which specific datasets you put into it.

In this article is a list of fifteen specific datasets from Mozilla Data Collective that we think belong in a serious TTS training stack in 2026. Some are large and provide an acoustic baseline. Some are small and provide a specific signal, an emotion, a script, a voice profile, that nothing else covers. All of them are downloadable today, all of them have clear licensing, and all of them are on Mozilla Data Collective.

The 15 datasets

  • Thorsten-Voice Dataset 2021.06 Emotional Contributor: Community | Licence: CC0-1.0 | Size: 380.80 MB | Task: TTS | Format: WAV, CSV
  • Urdu Multi-Speaker TTS Dataset Contributor: Community | Licence: CC-BY-NC-4.0 | Size: 514.54 MB | Task: TTS | Format: WEBM, TSV
  • LibriVox Italian TTS Female Voice Contributor: MDC Curators | Licence: CC0-1.0 | Size: 61.74 MB | Task: TTS | Format: MP3, TSV
  • LibriVox Czech TTS Female Voice Contributor: MDC Curators | Licence: CC0-1.0 | Size: 178.58 MB | Task: TTS | Format: MP3, TXT, TSV
  • Kokoro Speech Dataset Contributor: Community | Licence: LibriVox Public Domain | Size: 3.98 GB | Task: TTS | Format: FLAC
  • Yoruba-TTS-Dataset Contributor: Institute of African Digital Humanities | Licence: NOODL-1.0 | Size: 319.05 MB | Task: TTS | Format: MP3, TSV
  • Hausa-TTS-Dataset Contributor: Institute of African Digital Humanities | Licence: NOODL-1.0 | Size: 276.90 MB | Task: TTS | Format: MP3, TSV
  • isiXhosa-TTS-Dataset Contributor: Institute of African Digital Humanities | Licence: NOODL-1.0 | Size: 276.02 MB | Task: TTS | Format: MP3, TSV
  • Tiv-TTS-Dataset Contributor: Institute of African Digital Humanities | Licence: NOODL-1.0 | Size: 311.58 MB | Task: TTS | Format: MP3, TSV
  • Duala-TTS-Dataset Contributor: Institute of African Digital Humanities | Licence: NOODL-1.0 | Size: 141.26 MB | Task: TTS | Format: MP3, TSV
  • Bamun-TTS-Dataset Contributor: Institute of African Digital Humanities | Licence: NOODL-1.0 | Size: 219.97 MB | Task: TTS | Format: MP3, TSV
  • Saraiki 10 Hours TTS Dataset Contributor: MirasAI | Licence: CC-BY-NC-SA-4.0 | Size: 584.44 MB | Task: TTS | Format: WEBM, TSV
  • Chuvash TTS Contributor: Taruen | Licence: CC-BY-SA-4.0 | Size: 854.02 MB | Task: TTS | Format: PARQUET
  • Otomí (Hñähñu) TTS Voz Masculina Contributor: Community | Licence: CC-BY-SA-4.0 | Size: 119.54 MB | Task: TTS | Format: MP3, TXT, TSV
  • Central Kurdish TTS dataset 1.0 Contributor: The University of Melbourne | Licence: CC-BY-4.0 | Size: 293.45 MB | Task: TTS | Format: WAV

Not Scale but Curation

Production TTS in 2026 is no longer a scale problem but a curation problem. The fifteen datasets above won't, on their own, train a model but what they will do is let you build a deliberately diverse training mix that covers prosody, speaker variation, scripts, dialects, and the under-represented languages most commercial TTS still ignores. Mozilla Data Collective exists precisely to provide a platform for that diversity and unlock datasets from around the world that are more multicultural and multilingual.

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Mozilla Data Collective datasets now discoverable through CLARIN’s Virtual Language Observatory

New collaboration expands visibility for community-governed language datasets and improves exploration of linguistic resources, services and tools. Mozilla Data Collective datasets are now discoverable through CLARIN’s Virtual Language Observatory, making it easier for researchers, developers and language technology practitioners in Europe to find multilingual and community-centered datasets