ASR

Transcribe base64 or local audio files into written text.

1|Updated Jan 3, 2026
One-click install
npx skills add https://github.com/MO196931/documentosZai --skill asr-mo196931
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: ASR
Source: https://github.com/MO196931/documentosZai/tree/main/skills/ASR
Command: npx skills add https://github.com/MO196931/documentosZai --skill asr-mo196931

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires z-ai-web-dev-sdk, and includes scripts (resource) components.

What problem does it solve?

This Skill eliminates the tedious, error-prone manual work of transcribing audio recordings, saving hours of effort for teams and individuals working with spoken content like meetings, interviews, and voice notes.

Core Features & Use Cases

  • Multi-format Audio Transcription: Supports WAV, MP3, M4A, FLAC, and OGG audio files, plus base64 encoded audio input for flexible integration.
  • Batch Processing: Transcribe multiple audio files in a single run, ideal for processing large volumes of meeting recordings or interview files.
  • Use Case Example: A content team can use this Skill to transcribe 10 podcast episodes into searchable text in minutes, instead of spending hours manually typing out content.

Quick Start

Use the ASR skill to transcribe the audio file 'team-meeting-recording.wav' into accurate editable text.

Frequently Asked Questions about ASR

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I transcribe speech audio to text from a local file?

Audio transcription processes local audio file paths or base64 encoded audio input using the z-ai-web-dev-sdk backend to convert spoken speech into accurate editable text. It transcribes common formats like WAV, MP3, M4A, FLAC, and OGG.

What is the best way to transcribe multiple meeting recordings at once?

Batch audio transcription processes multiple audio files in a single run, converting large volumes of meeting recordings or interview files into searchable text efficiently to eliminate manual transcription labor.

Can I use base64 encoded audio for voice recognition processing?

Voice recognition supports base64 encoded audio input for flexible integration alongside local audio file paths. It uses the z-ai-web-dev-sdk backend service to process common audio formats into written text.

Does this speech-to-text transcription support MP3 and M4A formats?

Speech-to-text transcription supports common multi-format audio files including WAV, MP3, M4A, FLAC, and OGG. It processes these formats to generate accurate written text for podcast content, meeting notes, and voice memos.

When do I need audio transcription for accessibility text conversion?

Audio transcription is needed for accessibility audio text conversion when converting spoken content into written text. It eliminates manual transcription labor for interview documentation, podcast creation, and voice memo processing.

Are there limitations when processing large volumes of audio files for transcription?

Audio transcription requires base64 encoded audio input or local audio file paths and processes common formats via the z-ai-web-dev-sdk. While it supports batch processing of multiple files, output depends on backend service availability.