---
title: "init(trainingData:parameters:)"
framework: createml
role: symbol
role_heading: Initializer
path: "createml/mlsoundclassifier/init(trainingdata:parameters:)"
---

# init(trainingData:parameters:)

Creates a sound classifier with a training dataset represented by a data source.

## Declaration

```swift
init(trainingData: MLSoundClassifier.DataSource, parameters: MLSoundClassifier.ModelParameters = ModelParameters()) throws
```

## Parameters

- `trainingData`: An doc://com.apple.createml/documentation/CreateML/MLSoundClassifier/DataSource instance that contains a collection of labeled audio files.
- `parameters`: An doc://com.apple.createml/documentation/CreateML/MLSoundClassifier/ModelParameters-swift.struct instance you use to configure the model for the training session.

## Discussion

Discussion Use this initializer to train a sound classifier with an MLSoundClassifier.DataSource. For example, you can organize your audio files into labeled directories. See MLSoundClassifier.DataSource.labeledDirectories(at:). // Get the Documents directory URL. guard let documentsURL = FileManager.default.urls(for: .documentDirectory,                                                   in: .userDomainMask).first else {     fatalError("Can't find Documents directory.") }

// Build a URL to the ~/Documents/Sounds directory, which contains the training data. let soundsURL = documentsURL.appendingPathComponent("Sounds")

// The Sounds directory contains subdirectories, one for each class of sound. // Each subdirectory's name is the label for audio files it contains. // // Sounds // -- Laughter // -- Recording1.wav // -- Recording4.wav // -- ... // -- Applause // -- Recording2.wav // -- Recording5.wav // -- ...

// Create a data source from the Sounds directory. let trainingData = MLSoundClassifier.DataSource.labeledDirectories(at: soundsURL)

// Train a sound classifier with the data source. let soundClassifier = try MLSoundClassifier(trainingData: trainingData)