DocumentCode
270244
Title
Barista: A framework for concurrent speech processing by usc-sail
Author
Can, Doğan ; Gibson, J. ; Vaz, C. ; Georgiou, Panayiotis G. ; Narayanan, Shrikanth S.
Author_Institution
Signal Anal. & Interpretation Lab., Univ. of Southern California, Los Angeles, CA, USA
fYear
2014
fDate
4-9 May 2014
Firstpage
3306
Lastpage
3310
Abstract
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.
Keywords
message passing; public domain software; speech recognition; Apache License v2.0; Barista network; Kaldi speech recognition toolkit; complex training workflows; concurrent entities; concurrent speech processing; data flow; libcppa actor library; message passing; open-source framework; real-time speech recognizers; usc-sail; Computational modeling; Decoding; Feature extraction; Message systems; Speech; Speech processing; Speech recognition; C++; actor model; concurrency and distribution; open source; real-time speech recognition;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech and Signal Processing (ICASSP), 2014 IEEE International Conference on
Conference_Location
Florence
Type
conf
DOI
10.1109/ICASSP.2014.6854212
Filename
6854212
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