Basic Usage
Audio Chunk Interface
When to Use Audio Chunks
Custom Speech Recognition
Custom Speech Recognition
Use your own speech-to-text model:
Voice Analysis
Voice Analysis
Analyze voice characteristics:
- Voice activity detection (VAD)
- Pitch detection
- Emotion recognition
- Speaker identification
Audio Effects
Audio Effects
Apply real-time audio processing:
- Noise reduction
- Echo cancellation
- Voice enhancement
- Audio filtering
Recording
Recording
Save audio for later processing:
Working with Audio Data
Convert to Float32Array
Calculate Audio Level
Common Patterns
Recording Audio
Audio Level Monitoring
Performance Considerations
Audio Chunks Are Frequent
Audio Chunks Are Frequent
Audio chunks arrive many times per second:
Memory Management
Memory Management
Audio data accumulates quickly:
Processing Time
Processing Time
Keep processing fast:
Best Practices
Use Transcription API When Possible
Use Transcription API When Possible
Built-in transcription is optimized and easier:
Clone Buffers
Clone Buffers
ArrayBuffers may be reused:
Handle Errors
Handle Errors
Audio processing can fail:
Clean Up Resources
Clean Up Resources
Stop processing when done:
Permissions Required
AudioChunk Properties
Audio Format:
- Raw PCM audio data
- Mono (1 channel)
- Convert to
Float32Arrayfor processing
Troubleshooting
No Audio Chunks
No Audio Chunks
Check permission:
- Ensure MICROPHONE permission is set
- User must approve permission
- Check for permission errors in logs
Delayed Processing
Delayed Processing
Processing too slow:
- Keep processing under 20ms per chunk
- Use async processing with queues
- Optimize audio algorithms
Memory Issues
Memory Issues
Too much buffering:
- Limit stored chunks
- Process and discard quickly
- Donβt store entire recording in memory
Example: Simple Recording
Next Steps
Speech-to-Text
Use built-in transcription
Text-to-Speech
Generate voice output
Event Manager
Complete event API reference
Permissions
Learn about permissions

