Transcribe spoken audio to text with optional English translation and timestamps.
npx skills add https://github.com/Z43L/zeus-agent --skill whisper-z43l
Please help me install this Agent Skill. Skill: whisper Source: https://github.com/Z43L/zeus-agent/tree/main/optional-skills/mlops/whisper Command: npx skills add https://github.com/Z43L/zeus-agent --skill whisper-z43l
Whisper converts spoken audio into readable text, handling multilingual transcription and optional translation to English so you can avoid manual playback and note-taking.
Use case example: Transcribe a multilingual podcast and automatically translate it to English, then save the result as SRT subtitles for sharing or indexing.
Use the whisper skill to transcribe the attached file 'episode.mp3' and translate it to English.
High-intent search queries and answers about installing and using this skill.
Audio transcription converts spoken files into readable text while providing segment-level and word-level timestamps for precise alignment. This process supports batch processing and subtitle generation for recorded meetings or podcasts.
Yes, multilingual speech-to-text supports transcribing 99 languages and optionally translating non-English speech directly to English. This enables cross-language understanding and automated generation of English summaries.
Generating SRT subtitles involves transcribing the audio file and mapping the spoken content to timestamped text segments. You can specify the source language to optimize accuracy and automatically translate it to English for indexing.
Yes, speech recognition workflows support GPU acceleration to speed up batch audio processing. You can select model sizes from tiny to large or turbo, balancing processing speed and transcription accuracy based on your hardware.
You can improve speech recognition accuracy by providing specific prompts to guide the transcription model on technical or domain-specific terms. Selecting the correct language option also increases processing speed and output reliability.
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