Gajjar, Mrugesh R and Govindarajan, R and Sreenivas, TV (2008) Online Unsupervised Pattern Discovery in Speech Using Parallelization. In: Proceedings of Interspeech 2008, September 22--26, 2008, Brisbane, Australia.
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Segmental dynamic time warping (DTW) has been demonstrated to be a useful technique for finding acoustic similarity scores between segments of two speech utterances. Due to its high computational requirements, it had to be computed in an offline manner, limiting the applications of the technique. In this paper, we present results of parallelization of this task by distributing the workload in either a static or dynamic way on an 8-processor cluster and discuss the trade-offs among different distribution schemes. We show that online unsupervised pattern discovery using segmental DTW is plausible with as low as 8 processors. This brings the task within reach of today's general purpose multi-core servers. We also show results on a 32-processor system, and discuss factors affecting scalability of our methods.
|Item Type:||Conference Paper|
|Keywords:||Unsupervised pattern discovery;Dynamic time warping; Parallelization;Spoken language systems|
|Department/Centre:||Division of Electrical Sciences > Electrical Communication Engineering
Division of Information Sciences > Supercomputer Education & Research Centre
|Date Deposited:||19 Sep 2011 08:51|
|Last Modified:||19 Sep 2011 08:51|
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