Real-time multimodal conversational AI with audio support
GPT-4o Audio Preview enables seamless interaction across text and speech. It’s capable of real-time voice conversations and audio interpretation, making it ideal for assistants, accessibility tools, and voice interfaces.
Supports over 50 languages, covering approximately 97% of global speakers. Includes optimized tokenization for non-Latin languages.
GPT-4o is based on the Transformer architecture with multimodal enhancements. It integrates text and audio modalities seamlessly into a single model. The audio processing pipeline leverages voice activity detection (VAD) for real-time response generation.
The model was trained on diverse datasets spanning text and audio content. The audio corpus includes multilingual speech samples, music datasets, environmental sounds, and synthetic voice data.
While GPT-4o incorporates safeguards to reduce bias, its performance varies across tasks due to sensitivity in instructions or input quality. Known biases include inconsistent refusal rates for complex tasks like speaker verification or pitch extraction.
Achieved state-of-the-art scores on benchmarks like Massive Multitask Language Understanding (MMLU) with an 88.7 score. However, accuracy varies in specialized tasks such as music pitch classification.
Audio response time averages 320 milliseconds, enabling near-instantaneous conversational interactions.
Demonstrates strong generalization across multiple languages and accents but struggles with highly specific or ambiguous tasks like spatial distance prediction or audio duration estimation.
The model is available on the AI/ML API platform as "gpt-4o-audio-preview".
Detailed API Documentation is available on the AI/ML API website, providing comprehensive guidelines for integration
OpenAI has established ethical considerations in the model's development, focusing on safety and bias mitigation. The model has undergone extensive evaluations to ensure responsible use.
GPT-4o is available under commercial usage rights, allowing businesses to integrate the model into their applications.