咖啡师：南加州大学信息科学研究院用于并发语音处理的框架。
Barista: A Framework for Concurrent Speech Processing by USC-SAIL.
作者信息
Can Doğan, Gibson James, Vaz Colin, Georgiou Panayiotis G, Narayanan Shrikanth S
机构信息
Signal Analysis and Interpretation Lab, University of Southern California, CA 90089.
出版信息
Proc IEEE Int Conf Acoust Speech Signal Process. 2014 May;2014:3306-3310. doi: 10.1109/ICASSP.2014.6854212.
We present Barista, an open-source framework for concurrent speech processing based on the Kaldi speech recognition toolkit and the libcppa actor library. With Barista, we aim to provide an easy-to-use, extensible framework for constructing highly customizable concurrent (and/or distributed) networks for a variety of speech processing tasks. Each Barista network specifies a flow of data between simple actors, concurrent entities communicating by message passing, modeled after Kaldi tools. Leveraging the fast and reliable concurrency and distribution mechanisms provided by libcppa, Barista lets demanding speech processing tasks, such as real-time speech recognizers and complex training workflows, to be scheduled and executed on parallel (and/or distributed) hardware. Barista is released under the Apache License v2.0.
我们介绍了Barista，这是一个基于Kaldi语音识别工具包和libcppa actor库的用于并发语音处理的开源框架。借助Barista，我们旨在提供一个易于使用、可扩展的框架，用于构建高度可定制的并发（和/或分布式）网络，以处理各种语音处理任务。每个Barista网络指定了简单actor之间的数据流动，这些actor是通过消息传递进行通信的并发实体，其建模基于Kaldi工具。利用libcppa提供的快速且可靠的并发和分布式机制，Barista能够让诸如实时语音识别器和复杂训练工作流程等要求苛刻的语音处理任务在并行（和/或分布式）硬件上进行调度和执行。Barista是在Apache License v2.0许可下发布的。
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