H92-1035 will concentrate on modifying the N-best training algorithm to model context in
P13-2098 truth annotations . Effect of n-best training size on WER The size of the training
H92-1035 further and perform what we call N-best training , which is a form of discriminative
H92-1031 and presents a technique called N-best training which improves the performance
H92-1035 utterance transcription , because N-best training directly optimizes the performance
W08-0119 that the computation required for N-best training is significantly increased since
H92-1035 rate to 11.6 % . When we used the N-best training ( which used the SNN produced
H92-1035 confirming our belief that the N-best training is more effective than the 1-best
H92-1035 give an overall segment score . N-best Training In our latest version of the
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