AI Models for Speech

A structured overview of leading speech-to-text (STT) and text-to-speech (TTS) models, categorized by language support, quality, and access.

Speech-to-Text (STT / Automatic Speech Recognition)

Open Source / API

OpenAI Whisper

Highly robust model for transcription and translation in dozens of languages, trained on large amounts of diverse audio data.

  • Language: Multilingual (including Dutch)
  • Quality: High (estimated based on benchmarks)
  • Access: Open source weights / Cloud API
Open Source

Meta MMS (Massively Multilingual Speech)

Initially designed to make speech technology accessible for thousands of languages, including low-resource languages.

  • Language: Vast coverage (hundreds of languages)
  • Quality: Good to very good
  • Access: Open source (Hugging Face)

Text-to-Speech (TTS / Voice Synthesis)

Commercial / API

ElevenLabs Multilingual

Offers highly realistic and emotionally expressive voices with advanced voice cloning functionalities.

  • Language: Multilingual (fluent Dutch)
  • Quality: Exceptionally high
  • Access: Proprietary Cloud API
Open Source

Coqui TTS (XTTS)

Flexible open-source framework that supports zero-shot voice cloning and can be run locally.

  • Language: Multilingual (strong Dutch support)
  • Quality: Good
  • Access: Open source
Note on estimates: Quality ratings are based on qualitative benchmarks and community experiences, as exact metrics depend heavily on specific audio conditions and use cases. Also check out the LLMNet Directory for a wider range of AI tools.