AVPI VS SpeechSuper-API-Samples

Compare AVPI vs SpeechSuper-API-Samples and see what are their differences.

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AVPI SpeechSuper-API-Samples
2 1
197 33
- -
10.0 4.4
over 2 years ago 8 months ago
C# C#
GNU General Public License v3.0 only MIT License
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.

AVPI

Posts with mentions or reviews of AVPI. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-11-23.

SpeechSuper-API-Samples

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

What are some alternatives?

When comparing AVPI and SpeechSuper-API-Samples you can also consider the following projects:

soundfingerprinting - Open source audio fingerprinting in .NET. An efficient algorithm for acoustic fingerprinting written purely in C#.

mgpt - Multilingual Generative Pretrained Model

eviaca

cecilifier - A tool aiming to make it a little bit easier to learn Mono.Cecil

Avalonia - Develop Desktop, Embedded, Mobile and WebAssembly apps with C# and XAML. The most popular .NET UI client technology

NovelManager - Massive Exclusive Novels from multiple source all here in this app.

Chocolatey - Chocolatey - the package manager for Windows

OpenGNT - Open Greek New Testament Project; NA28 / NA27 Equivalent Text & Resources

MahApps.Metro - A framework that allows developers to cobble together a better UI for their own WPF applications with minimal effort.

silero-models - Silero Models: pre-trained speech-to-text, text-to-speech and text-enhancement models made embarrassingly simple

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