Feedback: speech-to-text-pre-recorded-audio

Documentation Feedback

Original URL: https://www.assemblyai.com/docs/speech-to-text/pre-recorded-audio
Category: speech-to-text
Generated: 05/08/2025, 4:23:36 pm

---

Claude Sonnet 4 Feedback

Generated: 05/08/2025, 4:23:35 pm

Technical Documentation Analysis & Feedback

Overall Assessment

This documentation provides good basic functionality but has several gaps that could frustrate users. The multi-language code examples are excellent, but the documentation lacks depth in critical areas.

🚨 Critical Issues

1. Missing Prerequisites & Setup

Problem: Users jump straight into code without understanding requirements.

Solution: Add a “Before You Start” section:

## Before You Start

### Prerequisites
- Valid AssemblyAI API key ([Get one here](link))
- Audio file in supported format (see [Supported Formats](#supported-formats))
- Programming environment set up with required dependencies

### Required Dependencies
- **Python**: `pip install assemblyai requests`
- **JavaScript**: `npm install assemblyai axios fs-extra`
- **C#**: NuGet packages for HTTP client and JSON handling

2. Incomplete Audio Format Information

Problem: No information about supported formats, file size limits, or quality requirements.

Solution: Add comprehensive format section:

## Supported Audio Formats

### File Formats
- **Audio**: MP3, WAV, FLAC, M4A, AAC, OGG
- **Video**: MP4, MOV, AVI, WMV (audio will be extracted)

### Specifications
- **Maximum file size**: 2GB
- **Sample rate**: 8kHz - 48kHz (16kHz+ recommended)
- **Bit depth**: 16-bit or 24-bit
- **Channels**: Mono or stereo

### Quality Guidelines
- Use lossless formats (WAV, FLAC) for best accuracy
- Ensure clear audio with minimal background noise
- Avoid heavily compressed files when possible

🔧 Structure & Navigation Issues

3. Poor Information Hierarchy

Current flow: Introduction → Code → Output → API Reference

Improved structure:

# Pre-Recorded Audio Transcription

## Overview
Brief description and use cases

## Before You Start
Prerequisites, setup, supported formats

## Quick Start
Simple example with explanation

## Step-by-Step Guide
Detailed walkthrough of the process

## Configuration Options
All available parameters explained

## Advanced Examples
Complex scenarios and best practices

## Troubleshooting
Common issues and solutions

## API Reference
Link to detailed API docs

📝 Content Gaps

4. Missing Configuration Explanation

Problem: The speech_model parameter appears without explanation.

Solution: Add configuration section:

## Configuration Options

### Speech Model Selection
```python
# Available models
config = aai.TranscriptionConfig(
    speech_model=aai.SpeechModel.slam_1,  # Latest model (recommended)
    # speech_model=aai.SpeechModel.best,   # Highest accuracy, slower
    # speech_model=aai.SpeechModel.nano,   # Fastest, lower accuracy
)

Model	Speed	Accuracy	Best For
slam-1	Fast	High	General use (recommended)
best	Slow	Highest	Critical accuracy needs
nano	Fastest	Good	Real-time applications

Additional Options

config = aai.TranscriptionConfig(
    speech_model=aai.SpeechModel.slam_1,
    language_detection=True,           # Auto-detect language
    punctuate=True,                   # Add punctuation
    format_text=True,                 # Format numbers, dates, etc.
    speaker_labels=True,              # Enable speaker diarization
)

### 5. **No Error Handling Guide**
**Problem**: Limited error handling examples.

**Solution**: Add comprehensive error handling:
```markdown
## Error Handling

### Common Errors and Solutions

#### Upload Errors
```python
try:
    transcript = aai.Transcriber().transcribe(audio_file)
except aai.TranscriptionError as e:
    if "file not found" in str(e).lower():
        print("❌ Audio file not found. Check the file path.")
    elif "unsupported format" in str(e).lower():
        print("❌ Unsupported audio format. See supported formats above.")
    elif "file too large" in str(e).lower():
        print("❌ File exceeds 2GB limit. Please compress or split the file.")

API Errors

if transcript.status == "error":
    error_message = transcript.error
    if "insufficient credit" in error_message.lower():
        print("❌ Insufficient credits. Please check your account balance.")
    elif "invalid api key" in error_message.lower():
        print("❌ Invalid API key. Please check your credentials.")
    else:
        print(f"❌ Transcription failed: {error_message}")

## 🎯 User Experience Improvements

### 6. **Add Processing Time Expectations**
```markdown
## What to Expect

### Processing Time
- **Typical**: 15-30% of audio duration
- **Example**: 10-minute audio = ~3-5 minutes processing
- **Factors**: File size, audio quality, selected model

### Status Updates
The transcription goes through these stages:
1. `queued` - Waiting to be processed
2. `processing` - Currently being transcribed
3. `completed` - Ready with results
4. `error` - Something went wrong

7. Improve Code Examples

Problem: Examples lack context and explanation.

Better approach:

## Step-by-Step Walkthrough

### Step 1: Upload Your Audio File
```python
# Option 1: Local file
audio_file = "./my-recording.mp3"

# Option 2: Remote URL (skip upload step)
# audio_file = "https://example.com/audio.mp3"

transcript = aai.Transcriber().transcribe(audio_file)

What happens here: AssemblyAI automatically uploads your local file to secure cloud storage and returns a temporary URL for processing.

Step 2: Configure Transcription Settings

config = aai.TranscriptionConfig(
    speech_model=aai.SpeechModel.slam_1,  # Use latest model
    language_detection=True,              # Auto-detect language
    speaker_labels=True,                  # Identify different speakers
)

transcript = aai.Transcriber(config=config).transcribe(audio_file)

Step 3: Handle the Results

if transcript.status == "completed":
    print("✅ Transcription successful!")
    print(f"Text: {transcript.text}")

    # Access additional features if enabled
    if hasattr(transcript, 'speaker_labels'):
        for utterance in transcript.utterances:
            print(f"Speaker {utterance.speaker}: {utterance.text}")

elif transcript.status == "error":
    print(f"❌ Error: {transcript.error}")

### 8. **Add Practical Examples**
```markdown
## Common Use Cases

### Meeting Transcription
```python
config = aai.TranscriptionConfig(
    speech_model=aai.SpeechModel.slam_1,
    speaker_labels=True,      # Identify speakers
    auto_chapters=True,       # Break into topics
    sentiment_analysis=True,  # Analyze tone
)

Podcast Processing

config = aai.TranscriptionConfig(
    speech_model=aai.SpeechModel.slam_1,
    auto_chapters=True,       # Generate episode segments
    entity_detection=True,    # Extract names, places, etc.
    content_safety=True,      # Flag sensitive content
)

## 🐛 Technical Issues

### 9. **Inconsistent Parameter Names**
**Problem**: `slam_1` vs `slam-1` inconsistency across examples.

**Solution**: Standardize and document both REST API and SDK formats:
```markdown
## Parameter Reference

| Feature | SDK Format | REST API Format |
|---------|------------|-----------------|
| Speech Model | `aai.SpeechModel.slam_1` | `"slam-1"`

---