Transcribes audio files and base64 payloads into searchable text transcripts.
npx skills add https://github.com/eesha000009-dev/Exam-Prep100 --skill asr-eesha000009-dev
Please help me install this Agent Skill. Skill: ASR Source: https://github.com/eesha000009-dev/Exam-Prep100/tree/main/skills/ASR Command: npx skills add https://github.com/eesha000009-dev/Exam-Prep100 --skill asr-eesha000009-dev
Converts spoken audio into accurate, searchable text so teams can avoid manual transcription work and unlock voice data for search, analysis, and accessibility.
Transcribe the audio file meeting.wav into a cleaned text transcript and return the transcription with a word count.
High-intent search queries and answers about installing and using this skill.
To transcribe audio files to text in an Express.js backend, you can process local WAV, MP3, M4A, or FLAC files using SDK integration. The workflow supports single files, batch jobs, and directory-wide processing.
Yes, you can use base64-encoded audio payloads for speech-to-text transcription. The system directly accepts base64 inputs alongside common audio formats like WAV and MP3 to generate searchable text transcripts.
Yes, this speech-to-text solution supports streaming and real-time audio processing. It handles both batch file transcription and streaming inputs, utilizing caching and basic file-size validation during processing.
The best way to batch transcribe a directory of audio recordings is using directory-wide processing features. This approach converts multiple spoken audio files into searchable text transcripts efficiently.
Yes, you need the z-ai-web-dev-sdk dependency to perform speech-to-text transcription. This SDK integration provides the core mechanism for converting spoken audio into accurate text.
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