Rhasspy

Piper TTS - LibriTTS-R (English)

Medium quality English voice with natural prosody. 63MB download.

0.02B parameterspipermit0.57GB - 0.57GB VRAM

About This Model

Piper TTS - LibriTTS-R (English) is a compact text-to-speech (TTS) model developed by Rhasspy, designed to generate natural-sounding English speech from written text. Despite its small size of just 0.02 billion parameters, this model delivers surprisingly high-quality audio output, making it an excellent choice for applications where computational resources are limited. The model's efficiency is particularly noteworthy, as it requires only 0.6 GB of VRAM, which means it can run smoothly on a wide range of devices, including older or lower-end hardware. This makes it a practical solution for developers and hobbyists who need a reliable TTS system without the need for powerful GPUs.

Compared to other models in its size class, Piper TTS - LibriTTS-R (English) punches well above its weight. It offers a balance between performance and resource consumption that is hard to match. While larger models might provide more nuanced and varied voices, this model's efficiency and quality make it a strong contender for real-world applications such as voice assistants, e-readers, and accessibility tools. Users looking for a lightweight, efficient, and effective TTS solution should seriously consider this model, especially if they are working with budget or mobile devices.

Check Your Hardware

See which quantizations of Piper TTS - LibriTTS-R (English) your hardware can run.

Quantization Options

QuantizationBitsFile SizeVRAM NeededRAM NeededQuality
ONNX160.073 GB0.57 GB1.07 GB
80%

Frequently Asked Questions

How much VRAM do I need to run Piper TTS - LibriTTS-R (English)?

Piper TTS - LibriTTS-R (English) requires 0.57GB VRAM minimum with ONNX quantization. For full precision, you need 0.57GB VRAM.

What is the best quantization for Piper TTS - LibriTTS-R (English)?

Q4_K_M offers the best balance of quality and VRAM usage. Q8_0 is near-lossless if you have enough VRAM.