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
Link To Document :
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