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SUMMARY:Configuring the Kaldi ASR toolkit for the Lengau Cluster
DTSTART;VALUE=DATE-TIME:20201130T120000Z
DTEND;VALUE=DATE-TIME:20201130T123000Z
DTSTAMP;VALUE=DATE-TIME:20260812T211358Z
UID:indico-contribution-1217@events.chpc.ac.za
DESCRIPTION:Speakers: Ewald Van der Westhuizen (Stellenbosch University)\n
 Kaldi] is an open source software project that was initiated by the Center
  for Language and Speech Processing\,Johns Hopkins University.  It is one 
 of the leading toolkits used for research in automatic speech recognition 
 (ASR).The toolkit employs current machine learning techniques such  a  dee
 p  neural  networks  and  is  capable  of  state-of-the-art  performance. 
   Kaldi  can  be  configured  for  a  single personal computer or a high p
 erformance computing (HPC) cluster using the Sun Grid Engine.  Although co
 nfiguring Kaldi for parallelisation on a cluster is well documented\, it i
 s assumed that the user has complete control.  A researcher may have the o
 ption to set up an in-house cluster with the advantage of complete control
 \, but maintaining the cluster can become a task that distracts from  the 
  research  work.   The  size  of  an  in-house  cluster is also limited by
  the resources and funds available to the researcher.  When the disadvanta
 ges outweigh the advantages\, migrating to a larger\, community-based clus
 ter with on-site support becomes attractive.  Because such clusters host u
 sers from various institutions and disciplines\, usage policies and restri
 ctions apply which were not applicable to the in-house cluster. These rest
 rictions affect how Kaldi can be used.\n\n[Full abstract added as a PDF at
 tachment.]\n\nhttps://events.chpc.ac.za/event/84/contributions/1217/
LOCATION:
URL:https://events.chpc.ac.za/event/84/contributions/1217/
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