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SpeakCrate

AI AppsText to SpeechOpen Source · CPU, NVIDIA GPU

SpeakCrate is an open-source, self-hosted text-to-speech API powered by Kokoro. It allows users to generate multilingual speech on their own hardware, offering a private and customizable solution for voice applications.

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SpeakCrate is an open-source, self-hosted text-to-speech API that empowers users to generate speech from text using their own hardware. Powered by Kokoro, it supports multilingual voices and provides a streaming audio feature. The API is OpenAI-compatible, allowing integration with existing tools without the need for an OpenAI account or API key. Users can deploy SpeakCrate using Docker on either CPU or NVIDIA GPU, making it versatile for different hardware setups.

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The platform offers 54 voices across nine languages, including English, Japanese, and Spanish, among others. Audio can be output in various formats such as MP3, WAV, and FLAC, and can be streamed as sentences are synthesized. SpeakCrate ensures privacy by processing text locally, which is ideal for applications requiring secure and private voice synthesis.

SpeakCrate is MIT licensed, and its deployment is facilitated through Docker, with options for offline use by caching models and voice files. The platform is part of a larger toolkit, the Self-Hosted AI Stack, which includes other AI tools for comprehensive local AI deployment. Users can try SpeakCrate in a Google Colab environment before deploying it locally.

The platform is designed for developers and organizations looking to integrate text-to-speech capabilities into their applications while maintaining control over their data. With its flexible deployment options and multilingual support, SpeakCrate is suitable for a wide range of applications, from narration and read-aloud tools to voice-enabled applications.

  • CategoryText to Speech
  • Pricing ModelOpen Source
  • DeploymentDocker
  • PlatformsCPU, NVIDIA GPU

  • Open-source and self-hosted

  • Powered by Kokoro

  • Multilingual voice support

  • OpenAI-compatible API

  • Docker deployment on CPU or NVIDIA GPU

  • Supports MP3, WAV, FLAC, Opus, AAC, PCM formats

  • Streaming audio and Server-Sent Events

  • Offline mode with cached models

  1. Deploy: Set up Docker on your server

  2. Configure: Choose voices and adjust settings

  3. Integrate: Use the API in your applications

  4. Optimize: Cache models for offline use

  • Narration
  • Read-Aloud Tools
  • Voice Applications
  • Language Learning
  • Private Voice Synthesis

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