Transcribe spoken audio into text across 99 languages using openai-whisper.
npx skills add https://github.com/Signmanal/VIGIL --skill whisper-signmanal
Please help me install this Agent Skill. Skill: whisper Source: https://github.com/Signmanal/VIGIL/tree/main/optional-skills/mlops/whisper Command: npx skills add https://github.com/Signmanal/VIGIL --skill whisper-signmanal
Manual transcription of audio content is time-consuming, especially for multilingual recordings, podcasts, or non-English meetings. This Skill automates speech-to-text conversion, cutting transcription work from hours to minutes without manual typing.
Use the whisper skill to transcribe the audio file 'team-standup.mp3' and output a timestamped English transcript.
High-intent search queries and answers about installing and using this skill.
To transcribe multilingual audio, this Skill processes spoken recordings and outputs written text across 99 supported languages. It automates speech-to-text conversion, eliminating manual typing for podcasts, meetings, and non-English audio content.
Yes, automatic English translation converts non-English speech to English text. This Skill handles multilingual audio processing and provides English translation output, enabling cross-team collaboration for global audiences.
Yes, speech-to-text conversion requires the openai-whisper Python library and ffmpeg for audio decoding. Optional GPU acceleration can be configured for faster inference when processing large audio files.
To generate timestamped transcripts, this Skill processes audio files and outputs time-stamped text. This format is ideal for creating SRT subtitle files, meeting notes, or audio editing workflows for global audiences.
Automated speech-to-text with optional GPU acceleration is the best way to transcribe a 1-hour podcast. This Skill processes long-form audio and generates accurate text transcripts in under 10 minutes, significantly faster than manual typing.
Speech-to-text works with low-resource languages through specialized model support. This Skill handles multilingual audio processing across 99 supported languages, ensuring accurate transcription even for less commonly spoken languages.
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