Convert spoken language into searchable text via the Nova-3 model.
npx skills add https://github.com/Shakudo-io/opencode-skills --skill deepgram-stt
Please help me install this Agent Skill. Skill: deepgram-stt Source: https://github.com/Shakudo-io/opencode-skills/tree/main/deepgram-stt Command: npx skills add https://github.com/Shakudo-io/opencode-skills --skill deepgram-stt
Deepgram STT speeds up and scales the conversion of spoken language into accurate, searchable text for real-time and batch audio workflows.
Transcribe an audio stream in real time using the Nova-3 model and return the text with basic formatting.
High-intent search queries and answers about installing and using this skill.
Real-time speech-to-text conversion uses the Nova-3 model via WebSocket streaming to transcribe live audio streams with sub-300ms latency. This approach supports live conversations, calls, and media analytics by returning text dynamically with smart formatting.
Speech-to-text diarization is fully supported for batch processing pre-recorded audio. The Nova-3 model identifies and separates speakers in audio files, which improves readability and generates structured meeting notes or archive tags.
Multi-language processing is supported across 36 languages for both real-time streaming and batch transcription. The Nova-3 model applies smart formatting and endpointing to deliver accurate, searchable text regardless of the spoken language.
Authenticating a WebSocket streaming transcription request requires a valid Deepgram API key. This key validates your access to the Nova-3 model for real-time audio processing and endpointing features.
The best way to apply smart formatting and endpointing to live transcriptions is using the Nova-3 model. It automatically punctuates and structures spoken language during real-time streaming, ensuring accurate and readable text output for live conversations.
Batch transcription should be used instead of real-time speech-to-text when processing pre-recorded audio files for meeting notes or archive tagging. Real-time streaming is better suited for live conversations requiring sub-300ms latency.
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jacardlConvert spoken language into text using local Whisper transcription.
