azzurra-voice

`azzurra-voice` is a state-of-the-art, highly expressive text-to-speech (TTS) model for the Italian language, developed by [Cartesia](https://cartesia.one/). Check out some audio samples in our [blog post](https://blog.cartesia.one/posts/introducing-azzurra-voice/). This model is the first release from the **Azzurra Project**, our initiative to build private, personal, and empathetic AI that feels Italian not just in language, but in culture, warmth, and presence. `azzurra-voice` was trained on thousands of hours of high-quality, diverse Italian speech, capturing a wide range of accents, prosodies, and conversational styles from across Italy. This model is released to empower researchers, developers, and makers to build more inclusive, local, and human-centered AI applications. * **Highly Expressive and Natural**: Generates speech with natural intonation and emotion, avoiding a robotic tone. * **Diverse Italian Dataset**: Trained on a comprehensive dataset that includes various regional accents and conversational patterns, making the output feel authentic and familiar. * **Efficient and High-Quality**: Optimized to run efficiently while delivering top-tier, 24,000 Hz speech quality. * **Open and Accessible**: Free, open-weight, and easy to integrate using the `transformers` library. You can run `azzurra-voice` with [`csm.rs`](https://github.com/cartesia-one/csm.rs), a high-performance Rust implementation for fast, real-time TTS inference. **Full-precision model:** csm.rs --model-id cartesia/azzurra-voice **Quantized Q8 model:** csm.rs --model-id cartesia/azzurra-voice --model-file q8.gguf Generating speech is straightforward using the Hugging Face `transformers` library. import torch from transformers import CsmForConditionalGeneration, AutoProcessor import soundfile as sf device = "cuda" if torch.cuda.is_available() else "cpu" processor = AutoProcessor.from_pretrained("cartesia/azzurra-voice") model = CsmForConditionalGeneration.from_pretrained("cartesia/azzurra-voice").to(device) text = "La sintesi vocale è un processo complesso" conversation = [ {"role": "user", "content": [{"type": "text", "text": text}]}, ] inputs = processor.apply_chat_template( conversation, tokenize=True, return_dict=True, ).to(device) audio_output = model.generate(**inputs, output_audio=True) waveform = audio_output[0].cpu().numpy() sf.write("output.wav", waveform, 24_000) * **Model Architecture**: `azzurra-voice` is a `sesame/csm-1b` * **Language**: Italian * **Sample Rate**: 24,000 Hz * **Training Data**: The model was trained on a proprietary dataset composed of thousands of hours of high-quality Italian speech. The dataset covers a wide demographic and geographic range within Italy. This model is licensed under the **Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0)**. This means: * **You are free to:** * **Share** — copy and redistribute the material in any medium or format. * **Adapt** — remix, transform, and build upon the material. * **Under the following terms:** * **Attribution** — You must give appropriate credit, provide a link to the license, and indicate if changes were made. * **NonCommercial** — You may not use the material for commercial purposes. * **ShareAlike** — If you remix, transform, or build upon the material, you must distribute your contributions under the same license as the original. For the full license text, please visit: [https://creativecommons.org/licenses/by-nc-sa/4.0/](https://creativecommons.org/licenses/by-nc-sa/4.0/) If you use `azzurra-voice` in your research, please cite it as follows: @software{Cartesia_Azzurra_Voice_2025, author = {Cartesia}, title = {{azzurra-voice: A State-of-the-Art Open Italian Text-to-Speech Model}}, month = {8}, year = {2025}, publisher = {Cartesia}, url = {https://huggingface.co/cartesia/azzurra-voice} }