Introducing Piper: A Fast, Local Neural Text-to-Speech System
Piper is an innovative text-to-speech (TTS) system that turns written text into natural-sounding speech. It is specifically optimized for performance on the Raspberry Pi 4, offering users a fast and efficient solution for speech synthesis. Piper is a project of the Open Home Foundation and is utilized in a wide array of applications, showcasing its versatility and reach.
Getting Started with Piper
To start using Piper, you can run a simple command line input that allows the system to convert a text string into a speech output file. To explore the quality of Piper's capabilities, you can listen to voice samples online or watch a comprehensive video tutorial by Thorsten Müller.
Voice Training and Availability
Piper utilizes the advanced VITS model for training its voices, which are then exported to onnxruntime. This approach allows for high-quality speech synthesis across various languages. Currently, Piper supports a broad range of languages, including but not limited to Arabic, Catalan, Chinese, and English. Each language requires both a model file and a configuration file to function correctly.
Installation Methods
For those interested in using Piper, there are flexible installation options. Users can either run Piper using Python or download pre-compiled binary releases compatible with various systems, such as AMD64, ARM64, and ARMv7. Detailed instructions for building Piper from the source are also available for advanced users.
How to Use Piper
To use Piper, follow these basic steps:
- Download and extract the necessary voice files for your desired language.
- Execute the Piper command with your text input, specifying the model and output file.
- Piper also supports additional features for advanced users, such as streaming audio output and accepting JSON input for dynamic speaker selection.
Real-world Applications
Piper is embraced by an array of projects, showcasing its real-world applicability. These include Home Assistant, a popular home automation platform, the NVDA screen reader for the visually impaired, and academic projects like image captioning for low-resource languages. The diversity of its usage highlights Piper's adaptability to different contexts and needs.
Training and Customization
The project provides resources for those interested in training new voices or customizing existing ones. Documentation and source code are also made available to support users in creating bespoke solutions tailored to their specific requirements.
Running Piper in Python
Piper can also be integrated into Python projects, allowing developers to incorporate speech synthesis capabilities into their custom applications effortlessly. Installation via pip enables this functionality, with additional support for GPU acceleration using onnxruntime-gpu for those who need even faster processing.
In summary, Piper is a powerful and versatile text-to-speech system suitable for a wide spectrum of applications, from personal projects on a Raspberry Pi to large-scale deployments in professional environments. Its focus on quality and ease of use makes it a standout choice in the world of speech synthesis technology.