Orpheus TTS: Text-to-Speech Towards Human Sounding Speech with Guided Emotion

Updated: March 20 2025 13:19
Canopy Labs Orpheus TTS open-source text-to-speech system leverages the capabilities of large language models to produce remarkably human-like speech that rivals—and in many cases surpasses—leading commercial solutions. Let's dive into what makes Orpheus TTS special and how you can start using it today.



Orpheus TTS is an innovative open-source text-to-speech system built on the Llama-3b backbone. What sets it apart from conventional TTS systems is its approach: instead of using traditional parametric or concatenative synthesis techniques, Orpheus harnesses the emergent capabilities of large language models for speech synthesis. This novel approach allows Orpheus to achieve levels of naturalness and expressivity previously seen only in premium closed-source solutions like Eleven Labs and PlayHT.

• Human-Like Speech: The most striking feature of Orpheus TTS is its ability to generate speech with natural intonation, emotion, and rhythm. Unlike many TTS systems that sound mechanical or flat, Orpheus produces voices that capture the nuances of human speech patterns. This includes appropriate pauses, emphasis, and tonal variations that make the generated speech sound genuinely human.
• Zero-Shot Voice Cloning: Perhaps one of the most impressive capabilities of Orpheus is its ability to clone voices without prior fine-tuning. This means you can generate speech that mimics specific vocal characteristics without extensive training data or complex setup processes. This feature opens up numerous creative and practical applications, from personalized content to accessibility solutions.
• Guided Emotion and Intonation: Orpheus gives you precise control over the emotional tone and speech characteristics through simple tags. Want your text to sound excited, contemplative, or concerned? Just add the appropriate emotion tags, and Orpheus adjusts the vocal delivery accordingly. This level of control allows for more engaging and context-appropriate speech synthesis.
• Low Latency Performance: With approximately 200ms streaming latency for real-time applications (reducible to around 100ms with input streaming), Orpheus is fast enough for interactive applications. This low latency makes it suitable for real-time dialogue systems, voice assistants, and other applications where immediate response is crucial.

The pretrained model uses Llama-3b as the backbone. It was trained on over 100k hours of English speech data and billions of text tokens. Training it on text tokens boosts its performance on TTS tasks as it maintains a great understanding of language.

Canopy use the exact same architecture, and training method, to train end-to-end speech models and they'll probably release an open source end-to-end speech model in the coming weeks. Orpheus offers multiple models to suit different needs:

• Finetuned Prod – A specialized model optimized for everyday TTS applications, delivering consistent, high-quality results.
• Pretrained – The base model trained on over 100,000 hours of English speech data, providing a solid foundation for speech synthesis.

For those eager to try Orpheus, the Orpheus-TTS-Local, a lightweight client for running the system on your local machine using LM Studio API. This approach ensures privacy and eliminates the need for cloud API keys. Getting started with Orpheus locally is straightforward:

1) Install LM Studio
2) Download the 2.36GB Orpheus TTS model (orpheus-3b-0.1-ft-q4_k_m.gguf) in LM Studio
3) Load the Orpheus model in LM Studio
4) Start the local server in LM Studio (default: http://127.0.0.1:1234)


Clone the repo and set up your Python environment:

git clone https://github.com/isaiahbjork/orpheus-tts-local.git
cd orpheus-tts-local
python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

Create the voice output using the local LM Studio server and save the audio locally:

python gguf_orpheus.py --text "As labor shortages continue to challenge industries worldwide, Google DeepMind, and entertainment pioneers like Disney Research suggests we're entering an era where robots will engage with us in increasingly sophisticated ways." --voice tara --output "output.wav"

Here is the voice generated from this prompt:

You can customize the generation with several options:

• --text: The text you want converted to speech
• --voice: Your chosen voice (default: tara)
• --output: Path for the output WAV file
• --temperature: Controls randomness (default: 0.6)
• --top_p: Sampling parameter (default: 0.9)
• --repetition_penalty: Prevents repetitive patterns (default: 1.1)

Orpheus comes with eight distinct voices to choose from, tara is recommended as the best overall voice for general use, also have leah, jess, leo, dan, mia, zac, and zoe for variety.

What truly elevates Orpheus beyond standard TTS systems is its support for emotional expression. You can add natural emotional elements to the speech by including supported emotional tags include < giggle >, < sign >, < gasp >, < laugh >, < chuckle >, < cough >, < sniffle >, < groan >, and < yawn >.

The combination of human-like speech, zero-shot voice cloning, emotional expressivity, and low latency performance makes Orpheus TTS a compelling option for a wide range of use cases. And with its straightforward local setup process, you can start exploring these capabilities today.

Canopy Labs: Orpheus TTS
Github: Orpheus TTS Open Source
Github: Orpheus TTS Local Open Source
Hugging Face: Orpheus TTS Models