kugelaudio-0-open

Open-source text-to-speech for European languages 7B parameter model powered by an AR + Diffusion architecture

License: MIT Python 3.10+ Hosted API

KugelAudio KI-Servicezentrum Berlin-Brandenburg Gefördert durch BMFTR

Motivation

Open-source text-to-speech models for European languages are significantly lagging behind. While English TTS has seen remarkable progress, speakers of German, French, Spanish, Polish, and dozens of other European languages have been underserved by the open-source community.

KugelAudio aims to change this. Building on the excellent foundation laid by the VibeVoice team at Microsoft, we've trained a model specifically focused on European language coverage, using approximately 200,000 hours of highly pre-processed and enhanced speech data from the YODAS2 dataset.

🏆 Benchmark Results: Outperforming ElevenLabs

KugelAudio achieves state-of-the-art performance, beating industry leaders including ElevenLabs in rigorous human preference testing. This breakthrough demonstrates that open-source models can now rival - and surpass - the best commercial TTS systems.

Human Preference Benchmark (A/B Testing)

We conducted extensive A/B testing with 339 human evaluations to compare KugelAudio against leading TTS models. Participants listened to a reference voice sample, then compared outputs from two models and selected which sounded more human and closer to the original voice.

German Language Evaluation

The evaluation specifically focused on German language samples with diverse emotional expressions and speaking styles:

• Neutral Speech: Standard conversational tones
• Shouting: High-intensity, elevated volume speech
• Singing: Melodic and rhythmic speech patterns
• Drunken Voice: Slurred and irregular speech characteristics

These diverse test cases demonstrate the model's capability to handle a wide range of speaking styles beyond standard narration.

OpenSkill Ranking Results

Based on 339 evaluations using Bayesian skill-rating system (OpenSkill)

Audio Samples

Listen to KugelAudio's diverse voice capabilities across different speaking styles and languages:

German Voice Samples

All samples are generated using pre-encoded voice embeddings.

Training Details

• Base Model: Microsoft VibeVoice
• Training Data: ~200,000 hours from YODAS2
• Hardware: 8x NVIDIA H100 GPUs
• Training Duration: 5 days

Supported Languages

This model supports the following European languages:

📊 Language Coverage Disclaimer: Quality varies significantly by language. Spanish, French, English, and German have the strongest representation in our training data (~200,000 hours from YODAS2). Other languages may have reduced quality, prosody, or vocabulary coverage depending on their availability in the training dataset.

Model Specifications

Quick Start

Installation

# Install with pip
pip install kugelaudio-open

# Or with uv (recommended)
uv pip install kugelaudio-open

Basic Usage

from kugelaudio_open import (
    KugelAudioForConditionalGenerationInference,
    KugelAudioProcessor,
)
import torch

# Load model
device = "cuda" if torch.cuda.is_available() else "cpu"
model = KugelAudioForConditionalGenerationI