gpt-4o-mini-transcribe
Version: 2025-03-20
The gpt-4o-mini-transcribe model is a highly efficient speech-to-text solution designed to deliver accurate audio transcriptions while optimizing for speed and resource consumption. This model offers significant improvements in word error rate and language recognition, making it particularly effective in scenarios involving accents, noisy environments, and varying speech speeds. gpt-4o-mini-transcribe is ideal for applications that require quick and reliable transcription services.
gpt-4o-mini-transcribe has been pretrained on specialized audio-centric datasets, which include diverse and high-quality audio samples, ensuring a deep understanding of speech nuances. This model supports a substantial context window of 16,000 tokens, allowing it to process longer audio inputs effectively. With a maximum output of 2,000 tokens, gpt-4o-mini-transcribe can generate detailed and comprehensive transcriptions. The training process incorporates rigorous enhancement techniques, including supervised fine-tuning and reinforcement learning, to optimize performance and accuracy.
Intended Use
Primary Use Cases
- Enhanced Customer Service: gpt-4o-mini-transcribe can be integrated into customer support systems to transcribe customer calls in real-time. This allows for more dynamic and comprehensive interactions, enabling support agents to quickly understand and resolve customer issues
- Meeting Transcription: The model is highly effective for transcribing meeting notes, capturing detailed discussions and decisions made during meetings. This can be particularly useful for creating accurate records of meetings, ensuring that all participants have access to the information discussed
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 Length16000
LicenseCustom
Training DataMay 2024
Last UpdatedApril 2025
Input TypeText,Audio
Output TypeText
PublisherOpenAI
Languages57 Languages