gpt-4o-mini-tts
Version: 2025-03-20
The gpt-4o-mini-tts model is an advanced text-to-speech solution designed to convert written text into natural-sounding speech. Leveraging the capabilities of GPT-4o, this model offers customizable voice output, allowing developers to instruct the model to speak in specific ways, such as "talk like a sympathetic customer service agent." gpt-4o-mini-tts is ideal for applications that require expressive and dynamic voice generation, such as audiobooks, podcasts, and interactive voice agents.
gpt-4o-mini-tts has been pretrained on diverse and high-quality text and audio datasets, ensuring a deep understanding of speech nuances and natural intonation. This model supports an input token limit of 2,000 tokens, allowing it to process substantial text inputs effectively. The training process incorporates rigorous enhancement techniques, including supervised fine-tuning and reinforcement learning, to optimize performance and accuracy.
Intended Use
Primary Use Cases
- Customer Service Automation: gpt-4o-mini-tts can be integrated into customer service systems to provide dynamic and empathetic voice responses. By instructing the model to speak in specific ways, such as "talk like a sympathetic customer service agent," businesses can enhance customer interactions and improve satisfaction.
- Content Creation and Publishing: The model is ideal for converting written content into engaging audio formats. This can be particularly useful for creating audiobooks, podcasts, and other spoken content, allowing creators to reach a broader audience and cater to different consumer preferences.
- Accessibility Enhancements: gpt-4o-mini-tts can be used to make digital content more accessible to individuals with visual impairments or reading difficulties. By converting text into natural-sounding speech, the model helps ensure that information is available to everyone, promoting inclusivity.
Out-of-Scope Use Cases
Our models are not specifically designed or evaluated for all downstream purposes. Developers should consider common limitations of language models as they select use cases, and evaluate and mitigate for accuracy, safety, and fairness before using within a specific downstream use case, particularly for high-risk scenarios. Developers should be aware of and adhere to applicable laws or regulations (including privacy, trade compliance laws, etc.) that are relevant to their use case.Model provider
This model is provided through the Azure OpenAI Service.Relevant documents
The following documents are applicable:Model Specifications
Context Length2000
LicenseCustom
Last UpdatedApril 2025
Input TypeText,Audio
Output TypeText,Audio
PublisherOpenAI
Languages57 Languages