TensorFlowTTS

At a glance

• Editor score
  3.0 / 10
• Pricing
  Open source
• Best for
  Engineers training and deploying custom TTS models
• Paid from
  Free
• Commercial use
  Yes
• Facts checked
  20 Sep 2026

• Where it wins

  • Supports Tacotron-2, FastSpeech, FastSpeech2 and multiple vocoders
  • Includes fine-tuning, multilingual training and single- or multi-GPU support
  • Offers TensorFlow Lite conversion, C++ inference and Android deployment examples

• Where it doesn't

  • Requires development and model-training work rather than ready-to-use speech generation
  • Primarily targets developers and researchers, not general end users
  • Documented requirements and feature updates are largely historical

Our verdict on TensorFlowTTS

TensorFlowTTS is an open-source speech-synthesis framework for TensorFlow 2 from TensorSpeech. It is aimed at developers and researchers who need to train, adapt and deploy text-to-speech models across Linux, iOS and Android. The project covers training, inference and mobile or embedded deployment, with Python installation and inference APIs. Its published language coverage includes English, French, Korean, Chinese and German, and its category specifications list WAV export and commercial use.

Its main strength is breadth within model development. TensorFlowTTS includes implementations of Tacotron-2, FastSpeech and FastSpeech2, alongside MelGAN, Multi-band MelGAN, Parallel WaveGAN and HiFi-GAN vocoders. Training and fine-tuning workflows support additional languages, while single- and multi-GPU training supports different development setups. For deployment, the project includes TensorFlow Lite model conversion, C++ inference examples and an Android deployment example. This combination suits teams that want to select an architecture, adapt a model and move toward mobile or embedded inference rather than consume a hosted voice API.

The trade-off is the amount of engineering involved. TensorFlowTTS is a development toolkit, so it fits organizations with the skills and infrastructure to manage model training, inference and deployment. It is less suitable for buyers seeking a finished end-user product or a ready-made workflow without model adaptation. The documented requirements and feature updates are largely historical, which matters when evaluating implementation effort and maintenance expectations. Choose TensorFlowTTS when open-source access, architecture choice, fine-tuning and deployment control matter most; choose an alternative when the priority is a turnkey speech product.

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TensorFlowTTS pricing

TensorFlowTTS fact sheet

Alternatives to TensorFlowTTS

• ElevenLabsAffordable voice cloning with multilingual generation, dubbing, streaming, and API access.9.4
• Google Cloud Text-to-SpeechA broad, API-only TTS service for developers building voice-enabled products.9.3
• Azure AI SpeechA broad, production-ready TTS platform for teams building voice applications.9.2

See all TensorFlowTTS alternatives →

Featured on iTechGuides

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Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026

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Last updated 7 Oct 2026 · How we research and update