ASR

Files (3)

• LICENSE.txt
• SKILL.md
• asr.ts · scripts/

SKILL.md (first lines)

---
name: ASR
description: Implement speech-to-text (ASR/automatic speech recognition) capabilities using the z-ai-web-dev-sdk. Use this skill when the user needs to transcribe audio files, convert speech to text, build voice input features, or process audio recordings. Supports base64 encoded audio files and returns accurate text transcriptions.
license: MIT
---

# ASR (Speech to Text) Skill

This skill guides the implementation of speech-to-text (ASR) functionality using the z-ai-web-dev-sdk package, enabling accurate transcription of spoken audio into text.

## Skills Path

**Skill Location**: `{project_path}/skills/ASR`

this skill is located at above path in your project.

**Reference Scripts**: Example test scripts are available in the `{Skill Location}/scripts/` directory for quick testing and reference. See `{Skill Location}/scripts/asr.ts` for a working example.

## Overview

Speech-to-Text (ASR - Automatic Speech Recognition) allows you to build applications that convert spoken language in audio files into written text, enabling voice-controlled interfaces, transcription services, and audio content analysis.

**IMPORTANT**: z-ai-web-dev-sdk MUST be used in backend code only. Never use it in client-side code.

## Prerequisites

The z-ai-web-dev-sdk package is already installed. Import it as shown in the examples below.

## CLI Usage (For Simple Tasks)

For simple audio transcription tasks, you can use the z-ai CLI instead of writing code. This is ideal for quick transcriptions, testing audio files, or batch processing.

### Basic Transcription from File

```bash
# Transcribe an audio file
z-ai asr --file ./audio.wav

# Save transcription to JSON file
z-ai asr -f ./recording.mp3 -o transcript.json

# Transcribe and view output
z-ai asr --file ./interview.wav --output result.json
```

### Transcription from Base64

```bash
# Transcribe from base64 encoded audio
z-ai asr --base64 "UklGRiQAAABXQVZFZm10..." -o result.json

# Using short option
z-ai asr -b "base64_encoded_audio_data" -o transcript.json
```

### Streaming Output

```bash
# Stream transcription results
z-ai asr -f ./audio.wav --stream
```

### CLI Parameters

- `--file, -f <path>`: **Required** (if not using --base64) - Audio file path
- `--base64, -b <base64>`: **Required** (if not using --file) - Base64 encoded audio
- `--output, -o <path>`: Optional - Output file path (JSON format)
- `--stream`: Optional - Stream the transcription output

### Supported Audio Formats

The ASR service supports various audio formats including:
- WAV (.wav)
- MP3 (.mp3)
- Other common audio formats

### When to Use CLI vs SDK

**Use CLI for:**
- Quick audio file transcriptions
- Testing audio recognition accuracy
- Simple batch processing scripts
- One-off transcription tasks

**Use SDK for:**
- Real-time audio transcription in applications
- Integration with recording systems
- Custom audio processing workflows
- Production applications with streaming audio

## Basic ASR Implementation

### Simple Audio Transcription

```javascript
import ZAI from 'z-ai-web-dev-sdk';
import fs from 'fs';

async function transcribeAudio(audioFilePath) {
  const zai = await ZAI.create();

  // Read audio file and convert to base64
  const audioFile = fs.readFileSync(audioFilePath);
  const base64Audio = audioFile.toString('base64');

  const response = await zai.audio.asr.create({
    file_base64: base64Audio
  });

  return response.text;
}

// Usage
const transcription = await transcribeAudio('./audio.wav');
console.log('Transcription:', transcription);
```

### Transcribe Multiple Audio Files

```javascript

From lucioupro2025/aprendiendo-abb-zai, MIT.

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