semvec/pypi-packages huggingface dataset:
voskIntentVoiceConvertHanzi 0.3.32
Offline open source speech recognition API based on Kaldi and Vosk
Requires Python: >=3

This is a Python module for Vosk.

Vosk is an offline open source speech recognition toolkit. It enables
speech recognition models for 17 languages and dialects - English, Indian
English, German, French, Spanish, Portuguese, Chinese, Russian, Turkish,
Vietnamese, Italian, Dutch, Catalan, Arabic, Greek, Farsi, Filipino.

Vosk models are small (50 Mb) but provide continuous large vocabulary
transcription, zero-latency response with streaming API, reconfigurable
vocabulary and speaker identification.

Vosk supplies speech recognition for chatbots, smart home appliances,
virtual assistants. It can also create subtitles for movies,
transcription for lectures and interviews.

Vosk scales from small devices like Raspberry Pi or Android smartphone to
big clusters.

# Documentation

For installation instructions, examples and documentation visit [Vosk
Website](https://alphacephei.com/vosk). See also our project on
[Github](https://github.com/alphacep/vosk-api).
DACPYLib 0.0.9
DAC Toolset package
Requires Python: >=3.6

# Introduction 
TODO: Give a short introduction of your project. Let this section explain the objectives or the motivation behind this project. 

# Getting Started
TODO: Guide users through getting your code up and running on their own system. In this section you can talk about:
1.	Installation process
2.	Software dependencies
3.	Latest releases
4.	API

# Build and Test
TODO: Describe and show how to build your code and run the tests. 

# Contribute
TODO: Explain how other users and developers can contribute to make your code better. 

If you want to learn more about creating good readme files then refer the following [guidelines](https://docs.microsoft.com/en-us/azure/devops/repos/git/create-a-readme?view=azure-devops). You can also seek inspiration from the below readme files:
- [ASP.NET Core](https://github.com/aspnet/Home)
- [Visual Studio Code](https://github.com/Microsoft/vscode)
- [Chakra Core](https://github.com/Microsoft/ChakraCore)