Transcribe multilingual audio to text across 99 languages.
npx skills add https://github.com/1thirteeng3/greenmoire --skill whisper-1thirteeng3
Please help me install this Agent Skill. Skill: whisper Source: https://github.com/1thirteeng3/greenmoire/tree/main/integrations/hermes-agent/skills/mlops/models/whisper Command: npx skills add https://github.com/1thirteeng3/greenmoire --skill whisper-1thirteeng3
Transcribing multilingual audio into accurate text is time-consuming and error-prone when done manually, especially across many languages. Whisper provides robust transcription and translation capabilities, enabling seamless capture of spoken content for accessibility, indexing, and content repurposing.
Transcribe a sample audio file to test Whisper's capabilities.
High-intent search queries and answers about installing and using this skill.
To transcribe multilingual audio to text, specify the target language or enable automatic language identification to generate accurate text outputs across 99 supported languages.
Yes, you can translate spoken audio to English text by enabling the translation task, which processes multilingual speech inputs and outputs the corresponding English text.
To generate timestamped outputs for podcast transcription, enable the optional timestamp feature during processing, which aligns the generated text segments with precise audio timings.
Yes, speech recognition model size affects hardware deployment; you can select from tiny to large models based on your CPU or GPU environment to optimize processing efficiency.
To improve video captions accuracy, provide an initial prompt containing specific vocabulary or context, which guides the speech recognition model to produce more accurate transcriptions.
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