---
license: mit
language:
  - lb
tags:
  - whisper
  - automatic-speech-recognition
  - luxembourgish
  - ctranslate2
  - faster-whisper
library_name: ctranslate2
pipeline_tag: automatic-speech-recognition
base_model: openai/whisper-large-v3-turbo
---

# Whisper Large V3 Turbo - Luxembourgish

A fine-tuned version of [OpenAI's Whisper Large V3 Turbo](https://huggingface.co/openai/whisper-large-v3-turbo) optimized for Luxembourgish speech recognition.

## Model Description

This model was fine-tuned on approximately 75 hours of Luxembourgish speech data, curated to be representative of diverse speaking contexts within the available data landscape for the language.

The model is provided in CTranslate2 format for efficient inference with [faster-whisper](https://github.com/SYSTRAN/faster-whisper) and compatible libraries.

### Model Details

- **Base Model:** openai/whisper-large-v3-turbo
- **Language:** Luxembourgish (lb)
- **Format:** CTranslate2
- **License:** MIT

## Intended Uses

- General automatic speech recognition (ASR) for Luxembourgish
- Audio and video transcription
- Speaker diarization pipelines (when combined with [PyAnnote](https://github.com/pyannote/pyannote-audio))

## Usage

### With faster-whisper

```python
from faster_whisper import WhisperModel

model = WhisperModel("ZLSCompLing/WhisperLargeTurboV3_Luxembourgish", device="cuda")

segments, info = model.transcribe("audio.wav", language="lb")
for segment in segments:
    print(f"[{segment.start:.2f}s -> {segment.end:.2f}s] {segment.text}")
```

### With WhisperX (for word-level timestamps and speaker diarization)

```python
import whisperx

model = whisperx.load_model("ZLSCompLing/WhisperLargeTurboV3_Luxembourgish", device="cuda")
audio = whisperx.load_audio("audio.wav")
result = model.transcribe(audio, language="lb")
```

## Technical Notes

When using this model with WhisperX and PyAnnote for speaker diarization, be aware of potential dependency conflicts between PyTorch, WhisperX, and PyAnnote. Depending on your setup, you may need both modern CUDA libraries and cuDNN 8 libraries installed.

For reference, see the [Sproochmaschinn](https://sproochmaschinn.lu) project, which uses this model in production.

## Citation

If you use this model, please cite:

```bibtex
@misc{zls2025whisperlb,
  title={Whisper Large V3 Turbo - Luxembourgish},
  author={Zenter fir d'Lëtzebuerger Sprooch},
  year={2025},
  publisher={Hugging Face},
  url={https://huggingface.co/ZLSCompLing/WhisperLargeTurboV3_Luxembourgish}
}
```

## Acknowledgments

Developed by [Zenter fir d'Lëtzebuerger Sprooch](https://zls.lu).

This model powers [Sproochmaschinn](https://sproochmaschinn.lu), a Luxembourgish speech processing platform.