elevenlabs-stt

To transcribe audio files and fix technical jargon automatically, this skill uses the ElevenLabs Scribe API for initial speech-to-text conversion, then applies a Claude-powered sub-agent for context-aware post-processing to correct domain-specific terminology.

Yes, you can use local memory or glossary files to correct speech-to-text transcriptions. The skill dynamically injects this context to identify and fix misinterpreted proper nouns and technical terms during the automated post-processing stage.

Yes, the ElevenLabs Scribe API supports transcribing technical meetings with speaker identification. It processes the audio recording and the skill's pipeline applies structural verification to ensure accurate documentation for interviews or lectures.

Context-aware speech-to-text post-processing is a secondary correction stage that uses project memory to fix transcription errors. You need it when standard AI models misinterpret technical jargon, proper nouns, or domain-specific terminology in your audio files.

Yes, you need an active ElevenLabs API key to transcribe video files into text. The skill relies on the Scribe API for the initial transcription stage before applying its automated context-aware corrections to the output.

Your transcription contains misinterpreted domain-specific terminology because standard AI speech-to-text models often lack project context. This skill solves the issue by applying context-aware post-processing using your local glossary files to automatically correct the errors.