KittenML

KittenTTS

AI#Text-to-Speech#ONNX#Machine Learning #Python

13,712

// summary

KittenTTS is an open-source, lightweight text-to-speech library designed for efficient voice synthesis on CPUs. It offers multiple model sizes ranging from 15M to 80M parameters, ensuring high-quality 24 kHz audio output with minimal disk footprint. The library includes built-in text preprocessing and supports adjustable speech speeds for versatile integration.

// technical analysis

Kitten TTS is a lightweight, open-source text-to-speech library designed for efficient voice synthesis on CPU-based environments. By leveraging ONNX for inference, the project enables high-quality audio generation without the need for dedicated GPU hardware, making it ideal for edge deployment. The library balances performance and accessibility by offering various model sizes ranging from 15M to 80M parameters, ensuring flexibility for different resource constraints.

// key highlights

Ultra-lightweight architecture with model sizes as small as 25 MB, perfect for resource-constrained edge devices.

CPU-optimized inference engine built on ONNX, eliminating the requirement for expensive GPU hardware.

Includes 8 distinct built-in voices, providing developers with immediate variety for their applications.

Features an integrated text preprocessing pipeline that automatically handles complex inputs like currencies, units, and numbers.

Supports adjustable speech speed parameters, allowing for dynamic control over the playback rate of synthesized audio.

Delivers high-quality 24 kHz audio output, ensuring clear and professional-sounding speech synthesis.

// use cases

Edge deployment of high-quality voice synthesis

CPU-optimized text-to-speech without GPU requirements

Customizable speech generation with eight built-in voices

// getting started

To begin, install the library using the provided pip command with the wheel file from the GitHub release. Once installed, initialize the KittenTTS class with your chosen model name and use the generate method to synthesize audio from text. You can then save the output as a file using standard libraries like soundfile or utilize the built-in generate_to_file method.