Barista: A Framework for Concurrent Speech Processing by USC-SAIL.
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.
Signal Analysis and Interpretation Lab, University of Southern California, CA 90089.
Doğan
D
Can
Signal Analysis and Interpretation Lab, University of Southern California, CA 90089.
James
J
Gibson
Signal Analysis and Interpretation Lab, University of Southern California, CA 90089.
Colin
C
Vaz
Signal Analysis and Interpretation Lab, University of Southern California, CA 90089.
Panayiotis G
PG
Georgiou
Signal Analysis and Interpretation Lab, University of Southern California, CA 90089.
Shrikanth S
SS
Narayanan
C++; actor model; concurrency and distribution; open source; real-time speech recognition