Feedback: guides-automatic-language-detection-separate

Documentation Feedback

Original URL: https://www.assemblyai.com/docs/guides/automatic-language-detection-separate
Category: guides
Generated: 05/08/2025, 4:43:17 pm

---

Claude Sonnet 4 Feedback

Generated: 05/08/2025, 4:43:16 pm

Technical Documentation Analysis & Feedback

Overall Assessment

This documentation provides a functional guide but has several gaps that could frustrate users and impact adoption. Here’s my detailed analysis with actionable improvements:

---

🚨 Critical Issues

1. Missing Error Handling

Problem: No error handling for API failures, network issues, or invalid responses.

Fix: Add comprehensive error handling:

def detect_language(audio_url):
    try:
        config = aai.TranscriptionConfig(
            audio_end_at=60000,
            language_detection=True,
            speech_model=aai.SpeechModel.nano,
        )
        transcript = transcriber.transcribe(audio_url, config=config)

        # Check if transcription was successful
        if transcript.status == aai.TranscriptStatus.error:
            raise Exception(f"Language detection failed: {transcript.error}")

        return transcript.json_response["language_code"]
    except Exception as e:
        print(f"Error detecting language: {e}")
        return None  # or fallback to default language

2. Incomplete Prerequisites

Problem: Assumes users know how to handle API keys securely.

Fix: Add security section:

## Prerequisites & Setup

### Required
- Python 3.7+
- AssemblyAI account ([sign up free](https://assemblyai.com/dashboard/signup))
- API key from your dashboard

### Security Best Practices
**⚠️ Never hardcode API keys in production code.**

Use environment variables:
```bash
export ASSEMBLYAI_API_KEY="your_api_key_here"

import os
import assemblyai as aai

aai.settings.api_key = os.getenv("ASSEMBLYAI_API_KEY")
if not aai.settings.api_key:
    raise ValueError("Please set ASSEMBLYAI_API_KEY environment variable")

---

📋 Structure & Content Improvements

3. Add Expected Outputs Section

Current: Users don’t know what to expect.

Add:

## Expected Output
Running the complete example will produce output like:

Identified language: pt Transcript: Olá, bem-vindos ao nosso podcast sobre tecnologia. Hoje vamos falar sobre…

Identified language: es
Transcript: Hola y bienvenidos a nuestro programa. En el episodio de hoy discutiremos…

Identified language: sl Transcript: Živjo, danes se pogovarjamo z Luko Dončićem o njegovi karieri…

Identified language: en Transcript: Today we’ll discuss the five most common sports injuries that athletes face…

### 4. **Add Cost Calculator**
**Current**: Mentions cost but no practical guidance.

**Add**:
```markdown
## Cost Estimation

### Language Detection Step
- **Rate**: $0.002 per file (first 60 seconds only)
- **Example**: 100 files = $0.20

### Full Transcription Costs
- **Universal Model**: $0.37/hour for supported languages
- **Nano Model**: $0.15/hour for all other languages

### Total Cost Calculator
```python
def estimate_cost(audio_duration_minutes, num_files, language_code):
    detection_cost = num_files * 0.002
    transcription_rate = 0.37 if language_code in supported_languages_for_universal else 0.15
    transcription_cost = (audio_duration_minutes / 60) * transcription_rate * num_files
    return detection_cost + transcription_cost

# Example: 100 files, 10 minutes each, Spanish content
total_cost = estimate_cost(10, 100, "es")
print(f"Estimated cost: ${total_cost:.2f}")

---

🔧 Technical Enhancements

5. Add Batch Processing Example

Problem: Current example processes files sequentially.

Add:

import asyncio
from concurrent.futures import ThreadPoolExecutor

def process_file_batch(audio_urls, max_workers=5):
    """Process multiple files concurrently for better performance."""
    def process_single_file(audio_url):
        try:
            language_code = detect_language(audio_url)
            if language_code:
                transcript = transcribe_file(audio_url, language_code)
                return {
                    "url": audio_url,
                    "language": language_code,
                    "transcript": transcript.text,
                    "model_used": "universal" if language_code in supported_languages_for_universal else "nano",
                    "status": "success"
                }
        except Exception as e:
            return {
                "url": audio_url,
                "error": str(e),
                "status": "failed"
            }

    with ThreadPoolExecutor(max_workers=max_workers) as executor:
        results = list(executor.map(process_single_file, audio_urls))

    return results

6. Add Validation & Fallback Logic

def detect_language_with_fallback(audio_url, fallback_language="en"):
    """Detect language with fallback to default if detection fails."""
    try:
        detected = detect_language(audio_url)
        if detected and detected != "unknown":
            return detected
    except Exception as e:
        print(f"Language detection failed: {e}")

    print(f"Falling back to default language: {fallback_language}")
    return fallback_language

---

📚 Documentation Structure Improvements

7. Add Navigation & Context

## Table of Contents
1. [When to Use This Approach](#when-to-use)
2. [Prerequisites & Setup](#prerequisites)
3. [Step-by-Step Implementation](#implementation)
4. [Cost Estimation](#cost-estimation)
5. [Error Handling](#error-handling)
6. [Performance Optimization](#performance)
7. [Troubleshooting](#troubleshooting)

## When to Use This Approach

**✅ Use separate language detection when:**
- Processing files in unknown languages
- Need cost optimization for mixed-language datasets
- Want to route different languages to appropriate models

**❌ Don't use when:**
- You already know the source language
- Processing short audio clips (< 60 seconds)
- Need real-time transcription

8. Add Troubleshooting Section

## Troubleshooting

### Common Issues

| Problem | Cause | Solution |
|---------|-------|----------|
| `KeyError: 'language_code'` | Language detection failed | Check audio quality, add error handling |
| `403 Forbidden` | Invalid API key | Verify API key in dashboard |
| `TimeoutError` | Large file processing | Implement retry logic with exponential backoff |
| Incorrect language detected | Poor audio quality | Use longer sample (increase `audio_end_at`) |

### Debug Mode
```python
# Enable detailed logging
import logging
logging.basicConfig(level=logging.DEBUG)

# Add debug info to functions
def detect_language_debug(audio_url):
    print(f"Processing: {audio_url}")
    config = aai.TranscriptionConfig(
        audio_end_at=60000,
        language_detection=True,
        speech_model=aai.SpeechModel.nano,
    )
    transcript = transcriber.transcribe(audio_url, config=config)
    print(f"API Response: {transcript.json_response}")
    return transcript.json_response.get("language_code", "unknown")

---

⚡ Quick Wins

1. Fix the typo: “the file then gets then routed” → “the file then gets routed”
2. Add links to related docs in the introduction
3. Include audio format requirements (supported formats, size limits)
4. Add a “Next Steps” section linking to advanced features
5. Include performance benchmarks (processing time expectations)

---