OtosakuFeatureExtractor-iOS 🎶

Welcome to the OtosakuFeatureExtractor-iOS repository! This lightweight Swift library is designed for log-Mel spectrogram extraction, leveraging the power of Accelerate and CoreML. With this tool, you can efficiently process audio signals and extract features for various applications in audio analysis and on-device AI.

Table of Contents

1. Features
2. Installation
3. Usage
4. Example
5. Contributing
6. License
7. Releases
8. Contact

Features

• Lightweight: Minimal footprint for fast performance.
• Swift-based: Easy integration into your iOS projects.
• CoreML Support: Seamless compatibility with machine learning models.
• Accelerate Framework: Utilizes Apple's Accelerate framework for optimized performance.
• Log-Mel Spectrogram Extraction: Perfect for audio signal processing and speech analysis.
• On-Device AI: Enables real-time processing without server dependency.

Installation

To get started with OtosakuFeatureExtractor-iOS, you can clone the repository or add it as a dependency in your project.

Using CocoaPods

Add the following line to your Podfile:

pod 'OtosakuFeatureExtractor-iOS'

Then run:

pod install

Manual Installation

1. Clone the repository:

   git clone https://github.com/DZAAAAH/OtosakuFeatureExtractor-iOS.git

2. Drag and drop the OtosakuFeatureExtractor folder into your Xcode project.

Usage

To use the library, simply import it into your Swift files:

import OtosakuFeatureExtractor

You can then create an instance of the feature extractor and start processing audio files.

Basic Example

Here’s a simple example of how to extract a log-Mel spectrogram from an audio file:

let audioFilePath = "path/to/audio/file.wav"
let featureExtractor = OtosakuFeatureExtractor()

do {
    let spectrogram = try featureExtractor.extractSpectrogram(from: audioFilePath)
    print("Spectrogram: \(spectrogram)")
} catch {
    print("Error extracting spectrogram: \(error)")
}

Example

To see the library in action, you can explore the example project included in the repository. This project demonstrates how to integrate the feature extractor into a simple iOS app.

Running the Example

1. Open the example project in Xcode.
2. Run the project on a simulator or device.
3. Select an audio file and observe the extracted log-Mel spectrogram displayed in the app.

Contributing

We welcome contributions to OtosakuFeatureExtractor-iOS! If you would like to contribute, please follow these steps:

1. Fork the repository.
2. Create a new branch for your feature or bug fix.
3. Make your changes and commit them.
4. Push your branch and create a pull request.

Please ensure that your code adheres to the project's coding standards and includes appropriate tests.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Releases

To download the latest release, please visit the Releases section. Here, you can find compiled binaries and other resources for your use.

Contact

For any inquiries or feedback, feel free to reach out via GitHub issues or contact the maintainer directly. Your input is valuable for the continuous improvement of this library.

---

Thank you for exploring OtosakuFeatureExtractor-iOS! We hope this library serves your audio processing needs effectively. If you encounter any issues or have suggestions for improvements, please don't hesitate to let us know. Happy coding!