CoreML-samples VS spokestack-ios

Compare CoreML-samples vs spokestack-ios and see what are their differences.

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CoreML-samples spokestack-ios
- 1
41 27
- -
0.0 2.2
almost 7 years ago over 2 years ago
Jupyter Notebook Swift
MIT License Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

CoreML-samples

Posts with mentions or reviews of CoreML-samples. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning CoreML-samples yet.
Tracking mentions began in Dec 2020.

spokestack-ios

Posts with mentions or reviews of spokestack-ios. We have used some of these posts to build our list of alternatives and similar projects.
  • I'm making personalized voice super easy to use in iOS, and need help testing!
    1 project | /r/iOSProgramming | 24 Apr 2021
    Some of you may already be familiar with the open-source Spokestack Swift libraries. Want to help shape a new product that will change what's possible with Voice AI for makers, enthusiasts, prototypers, and creators? We're beta testing a no-code AutoML service that will let you [redacted because we're not ready to say it publicly yet], using your own voice.

What are some alternatives?

When comparing CoreML-samples and spokestack-ios you can also consider the following projects:

CoreML-Models - Largest list of models for Core ML (for iOS 11+)

Tensorflow-iOS

SwiftSpeech - A speech recognition framework designed for SwiftUI.

Caffe2

SwiftCoreMLTools - A Swift library for creating and exporting CoreML Models in Swift

Awesome-Mobile-Machine-Learning - A curated list of awesome mobile machine learning resources for iOS, Android, and edge devices.

Bender - Easily craft fast Neural Networks on iOS! Use TensorFlow models. Metal under the hood.

AIToolbox - A toolbox of AI modules written in Swift: Graphs/Trees, Support Vector Machines, Neural Networks, PCA, K-Means, Genetic Algorithms

Swift-AI - The Swift machine learning library.