Main Purpose
Key Features
- Speech-to-Text API: Deepgram offers an API that developers can use to convert spoken language into written text.
- Advanced Speech AI: Deepgram's models provide fast and accurate transcription, along with contextual features like summarization, sentiment analysis, and topic detection.
- Live-streaming and Pre-recorded Audio Processing: Developers can process both live-streaming and pre-recorded audio using Deepgram's API.
- Multilingual Support: Deepgram's API supports transcription in dozens of languages.
- Custom Model Training: Developers can train custom models for unique use cases, allowing for more specialized speech recognition and transcription.
- Unified API for Deep NLU: Deepgram's API provides access to deep natural language understanding (NLU) capabilities.
- SDKs for Any Programming Language: Deepgram offers software development kits (SDKs) that allow developers to build applications using their preferred programming language.
- On-prem or Cloud Deployment: Deepgram provides options for deploying the API on-premises or on their managed cloud infrastructure.
- Scalable GPU Infrastructure: Deepgram offers scalable GPU infrastructure for training and inference, enabling efficient processing of large amounts of audio data.
Use Case
- Speech-to-Text Integration: Deepgram is ideal for developers who want to add speech recognition and transcription capabilities to their applications, such as voice assistants, transcription services, or audio analytics platforms.
- Multilingual Transcription: Deepgram's support for multiple languages makes it suitable for applications that require transcription in different languages, enabling global reach and localization.
- Customized Speech Recognition: Developers can train custom models to create specialized speech recognition systems tailored to specific domains or industries.