Converts spoken audio into text with optional English translation and timestamps.
npx skills add https://github.com/devMoez/titan --skill whisper-devmoez
Please help me install this Agent Skill. Skill: whisper Source: https://github.com/devMoez/titan/tree/main/optional-skills/mlops/whisper Command: npx skills add https://github.com/devMoez/titan --skill whisper-devmoez
Whisper solves the problem of converting spoken audio into accurate, readable transcripts and translations, so you can capture meetings, podcasts, and multilingual conversations without manual typing.
Use cases include transcribing podcasts and interviews, generating meeting notes, translating multilingual recordings for documentation, and preparing audio for downstream search or analysis (e.g., turning recordings into text for summaries).
Use the whisper skill to transcribe the attached audio file 'audio.mp3' and return the full text.
High-intent search queries and answers about installing and using this skill.
Transcribing audio files into text with timestamps involves using speech-to-text processing to generate segment and word-level markers for searchable records. This approach converts spoken recordings into readable text outputs suitable for downstream documentation and analysis.
Yes, translating multilingual podcast audio to English text is possible using automatic speech recognition with translation tasks. This converts non-English speech into consistent English text for localization and documentation across teams.
Speech-to-text processing supports automatic language detection for meetings across 99 languages. You can configure the system to detect the spoken language automatically or specify the language explicitly to improve transcription accuracy.
Processing batch audio recordings for transcription uses programmatic handling to convert multiple spoken audio sources into readable text. This allows you to process podcasts, interviews, and meetings systematically for downstream search and analysis.
Improving transcription quality for noisy audio involves selecting configurable model sizes, providing explicit language hints, and using initial prompts. These tuning options help the speech-to-text engine accurately process challenging audio recordings.
silva2kandTranscribe audio files to text locally using the Whisper CLI.
dingdyanTranscribes audio files into text using OpenAI's Whisper API.
buda-aiExtract and enhance audio from video files for MP3/WAV/AAC output.
superfhpTranscribe spoken audio to text and translate it to English using OpenAI's Whisper model.
