Transcribes multilingual audio into timestamped text or English translations.
npx skills add https://github.com/afel6/scal-ai-pipeline --skill whisper-afel6
Please help me install this Agent Skill. Skill: whisper Source: https://github.com/afel6/scal-ai-pipeline/tree/main/hermes_skills_library/mlops/models/whisper Command: npx skills add https://github.com/afel6/scal-ai-pipeline --skill whisper-afel6
Converts spoken audio into accurate, timestamped text and optionally into English translations, removing the manual work of listening and transcribing recordings while preserving segment metadata for downstream analysis.
Transcribe the audio file meeting.mp3 to English text using the turbo Whisper model and save the transcript to transcript.txt.
High-intent search queries and answers about installing and using this skill.
Yes, speech-to-text transcription supports direct translation to English alongside multilingual transcription. It processes audio from podcasts and meetings across 99 languages, outputting translated text with segment metadata for analytics pipelines.
You need ffmpeg for audio extraction and Python libraries like openai-whisper or faster-whisper. Optional GPU acceleration improves latency and VRAM handling for large transcription models, but batch processing can run on CPU with reduced speed.
Yes, batch processing podcast recordings is supported. The transcription handles multilingual audio, generating searchable text with timestamps and segment metadata suitable for meeting notes automation and RAG pipelines.
Generating word-level timestamps for audio subtitles requires a robust speech-to-text mechanism that outputs fine-grained timing metadata. This approach processes lecture or meeting audio to produce segment data for subtitle formatting and analytics.
Faster-whisper and openai-whisper offer model-size tradeoffs for speed and accuracy in speech-to-text tasks. Choosing depends on latency requirements, VRAM availability, and whether you use GPU acceleration for large transcription models.
SignmanalTranscribe spoken audio into text across 99 languages using openai-whisper.
hmzainjamilConvert audio and video recordings into transcripts, subtitles, and meeting notes.
pmcdowallTranscribe spoken audio into timestamped text across 99 languages.
bomberoxenviosdosruedasBuild speech transcription pipelines using Whisper models and cloud ASR services.
