Transcribe and translate multilingual audio across 99 languages.
npx skills add https://github.com/Plaidmustache/hermes-nulab --skill whisper-plaidmustache
Please help me install this Agent Skill. Skill: whisper Source: https://github.com/Plaidmustache/hermes-nulab/tree/main/optional-skills/mlops/whisper Command: npx skills add https://github.com/Plaidmustache/hermes-nulab --skill whisper-plaidmustache
Whisper is designed to convert spoken language into text across many languages, enabling automated transcription, translation, and multilingual audio processing without manual transcription.
Install Whisper and run a transcription on your audio file to generate text.
High-intent search queries and answers about installing and using this skill.
To transcribe audio files into text automatically, you can use Whisper for multilingual speech-to-text processing. It requires Python packages like openai-whisper, torch, and transformers to load models and generate accurate transcripts from your audio.
Yes, you can translate spoken audio to English using speech recognition. Whisper supports translation to English and language identification across 99 languages, enabling automated multilingual audio processing without manual transcription.
The best way to generate podcast transcripts and meeting notes is using automated speech recognition tools like Whisper. It converts spoken language into text across 99 languages, handling diverse audio workflows for accessibility captions and notes.
Multilingual speech-to-text transcription works for accessibility captions by converting spoken audio into accurate text. Whisper supports 99 languages, allowing you to automate caption generation for podcasts, meetings, and diverse audio content.
Yes, you need Python and machine learning frameworks to run audio transcription with Whisper. The implementation requires installing openai-whisper, transformers, and torch to load speech recognition models and process audio files.
Whisper supports 99 languages for speech recognition, enabling reliable multilingual transcription and translation. It applies to diverse domains including podcast transcription, meeting notes, accessibility captions, and multilingual audio workflows.
math-incTranscribe audio into text using Whisper multilingual speech recognition models.
trpc-groupTranscribe audio files into text or JSON using the Whisper model.
GitnappTranscribe spoken audio into text with timestamps using Whisper.
lvhuanidTranscribe spoken audio into written text using the z-ai-web-dev-sdk.
