Orpheus TTS - an open-source AI speech synthesis system that supports multiple speech styles.
Orpheus TTS is an open-source text-to-speech (TTS) system based on the Llama-3b architecture. Orpheus TTS supports generating natural, emotional, and near-human-level speech, and features zero-sample speech cloning capabilities, requiring no pre-production...
What is Orpheus TTS?
Orpheus TTS is an open-source text-to-speech (TTS) system based on the Llama-3b architecture. Orpheus TTS supports the generation of natural, emotional, and near-human-level speech, featuring zero-shot speech cloning capabilities, eliminating the need for pre-training, and mimicking specific speech patterns. With a latency as low as approximately 200 milliseconds, Orpheus TTS is suitable for real-time applications. Orpheus TTS provides various pre-trained and fine-tuned models, allowing users to customize training based on limited data to meet the speech synthesis needs of different scenarios.
Main functions of Orpheus TTS
- Near-human level speechProvides a natural tone, emotion, and rhythm.
- Zero-sample speech cloningNo pre-trained cloned speech is required.
- Guiding emotions and tone: Controlling speech and emotional features based on simple labels.
- low latencyThe streaming latency for real-time applications is approximately 200 milliseconds, while input streaming processing can reduce the latency to approximately 100 milliseconds.
- Supports multiple voice stylesIt offers a variety of preset voice styles (such as "tara", "leah", etc.), and users can choose different voice characters to synthesize according to their needs.
Orpheus TTS Technical Principles
- Based on Llama architectureLlama-3b serves as the foundational model architecture, combining powerful language understanding and generation capabilities to better handle the complexities of natural language in speech synthesis.
- Large-scale data trainingThe model was pre-trained on over 100,000 hours of English speech data and billions of text tags, learning the rhythm, intonation, and emotional expression of the language based on a large amount of speech and text data.
- Non-stream word segmenter and SNAC decoderUsing a non-streaming (CNN-based) word segmenter and an SNAC decoder, we achieve uninterrupted streaming speech synthesis based on an improved decoder, avoiding the audio "pop" problem that may occur in traditional methods.
- Real-time streaming inferenceBased on a high-efficiency vLLM (unconventional language model) implementation, it can quickly generate speech on GPUs, support real-time output and input streaming processing, and meet the needs of low-latency real-time applications.
- Emotional and intonation guidanceThe model incorporates emotion tags and text-speech pairs into the training data to learn speech features under different emotional states, and supports user-labeled control of speech emotion and intonation.
Orpheus TTS project address
- Project official website:https://canopylabs.ai/model-releases
- GitHub repository:https://github.com/canopyai/Orpheus-TTS
- HuggingFace model library:https://huggingface.co/collections/canopylabs/orpheus-tts
Application scenarios of Orpheus TTS
- audiobooks and podcastsConvert text into natural speech to generate audio content.
- Virtual AssistantIt provides natural voice interaction and supports real-time dialogue.
- gameGenerate personalized voices for game characters to enhance immersion.
- educate: To assist teaching and help students with listening training.
- Accessibility: To help visually impaired people obtain information through voice.