There are many packages in Python which allow one to perform real-time processing on audio data. Unfortunately, due to the synchronous nature of the language, there lacks a framework which allows for distributed parallel processing of the data without requiring a large programming overhead and in which the data acquisition is not blocked by subsequent processing operations. This work improves on packages used for audio data collection with a light-weight backend and a simple interface that allows for distributed processing through a socket-based structure. This is intended for real-time audio machine learning and data processing in Python with a quick deployment of multiple parallel operations on the same data, allowing users to spend less time debugging and more time developing.

翻译：Python中有许多包可用于对音频数据进行实时处理。然而，由于该语言的同步特性，目前缺乏一种框架，既能在无需大量编程开销的情况下实现数据的分布式并行处理，又能确保数据采集不会被后续处理操作阻塞。本文通过一个轻量级后端和基于套接字结构的简单接口，改进了用于音频数据采集的现有包。该设计旨在支持Python中的实时音频机器学习与数据处理，能够快速部署对同一数据的多重并行操作，从而让用户将更多时间用于开发而非调试。