What is SeedRealtime
SeedRealtime is a native audio-video full-duplex large model launched by ByteDance's Seed team. Based on a unified architecture, it natively integrates audio, video, and text to achieve all-modal real-time interaction while seeing, listening, and speaking simultaneously. The model has three core breakthroughs: joint audio-video understanding, proactive interaction, and smooth conversational rhythm. End-to-end evaluations show that conversational rhythm issues are reduced by half compared to cascaded models. It has now been fully launched onDoubao App, becoming the industry's first audio-video full-duplex AI product to be deployed at scale.
Main features of SeedRealtime
- Joint audio-video understanding: Native deep fusion of sound, visuals, and temporal information, capable of resolving homophone ambiguity in combination with visual scenes and accurately understanding temporal references, achieving integrated perception of what is seen, heard, and said.
- Proactive interaction capability: Possesses continuous environmental awareness and proactive expression capabilities, able to proactively remind users when the visual state changes and invoke tools to integrate into expression, upgrading passive response to proactive collaboration.
- Smooth interaction rhythm: Perceives the user's conversation state and communication rhythm in real time, naturally picking up, pausing, and responding at appropriate moments, with strong anti-interference capability, able to distinguish nearby chatter from background noise.
- Multi-person scene recognition: In multi-person, noisy environments, it simultaneously recognizes faces, distinguishes sound sources, understands content, and continuously maps each person's voice to their identity.
Technical principles of SeedRealtime
- End-to-end unified modeling: Adopts an end-to-end unified audio-video modeling framework, incorporating perception, understanding, decision-making, and expression into the same model synchronously, avoiding the multi-stage information loss and latency accumulation of ASR→VLM→TTS in cascaded systems.
- Native full-duplex interaction: Does not rely on external VAD rules to determine turns; the model itself continuously decides the dialogue state and timing based on multimodal information streams, truly achieving "speaking while listening" rather than the question-and-answer half-duplex mode.
- Audio-video temporal alignment: Unifies sound, visuals, and temporal information in modeling, combining the current scene, gestures, gaze, and historical actions to understand user intent, completing cross-modal disambiguation and reference resolution.
- Engineering low-latency optimization: Through chunked audio-video input and streaming generation, combined with efficient quantization and inference optimization, continuously compresses the end-to-end latency from "hearing—understanding—responding."
How to use SeedRealtime
- Update Doubao App: UpdateDoubao Appto the latest version.
- Enter voice call: After opening the App, click the "call" button in any dialog box.
- Switch to video mode: After entering the call interface, enable camera and microphone permissions and switch to video call.
- Start real-time interaction: Speak naturally while showing the scene, and the model synchronously perceives the audio-video stream and responds in real time.
- Use proactive observation: You can issue continuous observation instructions, and the model will proactively remind you when the target appears or the visuals change.
Core advantages of SeedRealtime
- End-to-end unified architecture: Adopts a single model to natively integrate audio, video, and text, eliminating the information loss and latency accumulation caused by multiple modules connected in series in cascaded systems.
- Native full-duplex interaction: It does not rely on external VAD rules; the model autonomously and continuously judges conversation timing based on multimodal information streams, truly achieving "listening while speaking" rather than one-question-one-answer exchanges.
- Joint audio-video understanding: It deeply fuses sound, visuals, and temporal information, and can use visual scenes to disambiguate homophones and accurately resolve cross-modal references such as "this" and "there."
- Proactive environmental perception: It has continuous visual observation capability and can proactively remind when the scene state changes or a target appears, upgrading interaction from passive response to proactive collaboration.
- Smooth anti-interference rhythm: It perceives the user's conversation state in real time and accurately distinguishes casual chat from formal questions in noisy environments, with stutters and false triggers reduced by half compared with cascaded models.
SeedRealtime project address
- Project official website：https://seed.bytedance.com/en/seedrealtime
Comparison of SeedRealtime with similar competing products
| Dimension | SeedRealtime | Gemini Live |
|---|---|---|
| Developer | ByteDance Seed Team | Google DeepMind |
| Architecture | End-to-end unified audio-video modeling, integrating perception, understanding, decision-making, and expression | Native multimodal, supporting simultaneous input of audio + video + images + text |
| Full duplex | Native full duplex, not relying on external VAD, autonomously judging conversation timing | Full-duplex real-time bidirectional voice, supporting proactive audio output |
| Chinese optimization | Deeply optimized, strong in homophone disambiguation and Chinese context understanding | General multilingual support (200+ languages), Chinese is not specially optimized |
| Proactive interaction | Continuous environmental perception, proactively reminding and invoking tools when the scene changes | Supports proactive speaking and tool invocation, with limited visual proactivity |
| Anti-interference | Strong, can accurately distinguish casual chat, background noise, and formal questions | Built-in noise processing, moderate performance in complex noisy environments |
| Visual understanding | Joint audio-video temporal modeling, accurately parsing gestures, references, and dynamic scenes | Native video stream processing, supporting real-time camera image analysis |
| Latency performance | End-to-end low latency, conversation rhythm issues reduced by half compared with cascaded models | First audio latency about 200-320ms, response speed leading the industry |
| Ecosystem integration | Deep integration with Doubao App | System-level integration with Google Workspace, Search, Meet, and Android |
SeedRealtime application scenarios
- Smart tour guide: Continuously observes exhibit images in a museum and proactively explains historical background and craft details when a target appears.
- Foreign language practice partner: Combines visuals to correct pronunciation in real time and give example sentences, always staying focused on the target learner in noisy environments.
- Device operation guidance: When operating complex equipment, corrects errors in real time based on visual state changes and provides adjustment suggestions.
- Travel information assistant: Recognizes flight information on large screens in noisy airport environments, answers arrival times, and provides route guidance.
- Children's education tutoring: While accompanying children in learning, observes screen content in real time to correct pronunciation without being disturbed by background voices.