---
title: Classifying Sounds in an Audio Stream
framework: soundanalysis
role: article
role_heading: Article
path: soundanalysis/classifying-sounds-in-an-audio-stream
---

# Classifying Sounds in an Audio Stream

Identify individual sounds in an audio data stream, such as from a microphone, with an audio stream analyzer.

## Overview

Overview Use an SNAudioStreamAnalyzer to recognize sounds, such as human speech, music, and singing, by processing an audio stream, such as from a microphone. For example, a sound recording app can use an audio stream analyzer to show a visual label for sounds the app identifies in real time. This article builds on the Classifying Sounds in an Audio File article, including: Creating an SNClassifySoundRequest Implementing a type that conforms to SNResultsObserving Start an Audio Engine The Audio Engine API simplifies audio-related tasks, including capturing audio data with a microphone. Capture audio data from the device’s default microphone: Create an AVAudioEngine instance. Save a reference to the microphone’s AVAudioFormat instance. Begin the audio pipeline’s data flow by calling the engine’s start() method. func startAudioEngine() {     // Create a new audio engine.     audioEngine = AVAudioEngine()

// Get the native audio format of the engine's input bus.     inputBus = AVAudioNodeBus(0)     inputFormat = audioEngine.inputNode.inputFormat(forBus: inputBus)          do {         // Start the stream of audio data.         try audioEngine.start()     } catch {         print("Unable to start AVAudioEngine: \(error.localizedDescription)")     } } When you create an audio engine instance, its default inputNode accesses audio data from the device’s default microphone. important: To access the device’s microphone in iOS or watchOS, add a description for the NSMicrophoneUsageDescription key in your project’s Info.plist file. Create a Stream Analyzer Analyze the microphone audio by configuring an SNAudioStreamAnalyzer to the input device’s native PCM (pulse code modulation) audio format. // Create a new stream analyzer. streamAnalyzer = SNAudioStreamAnalyzer(format: inputFormat) Audio stream analyzers only work with audio data in the PCM format, unlike SNAudioFileAnalyzer instances. important: If the input device’s audio format changes, you must discard the current SNAudioStreamAnalyzer and create a new one that matches the input’s updated audio format. Create a sound classification request and a results observer (see Classifying Sounds in an Audio File) and add them to the stream analyzer by calling add(_:withObserver:). // Add a sound classification request that reports to an observer. try streamAnalyzer.add(classifySoundRequest,                        withObserver: resultsObserver) Analyze the Sound Data with an Audio Tap Access the microphone’s audio data by creating a tap to the audio engine’s input node. func installAudioTap() {     audioEngine.inputNode.installTap(onBus: inputBus,                                      bufferSize: 8192,                                      format: inputFormat,                                      block: analyzeAudio(buffer:at:)) } Keep your app responsive and the audio engine operating efficiently by running the stream analyzer on a dedicated dispatch queue. Separating the work frees the audio engine to process incoming audio data while the request analyzes the previous audio buffers. let analysisQueue = DispatchQueue(label: "com.example.AnalysisQueue")

...

func analyzeAudio(buffer: AVAudioBuffer, at time: AVAudioTime) {     analysisQueue.async {         self.streamAnalyzer.analyze(buffer,                                     atAudioFramePosition: time.sampleTime)     } } The stream analyzer sends the results to your SNResultsObserving instance.

## See Also

### Audio analyzers

- [Classifying Sounds in an Audio File](soundanalysis/classifying-sounds-in-an-audio-file.md)
- [SNAudioFileAnalyzer](soundanalysis/snaudiofileanalyzer.md)
- [SNAudioStreamAnalyzer](soundanalysis/snaudiostreamanalyzer.md)