ICSI BN Feature Matrix

Matrix of 2000HU systems trained on 37h showing all combinations of rasta, per-utterance normalization and deltas, both alone and in combination with RNN1:

This table shows the overall word-error rate for the following conditions:

• MLPs have 2000 hidden units and 54 output units
• Nets have 13x9=117 input units for `plain' features, and 26x9=234 input units for features+deltas.
• Training set is randomized half of 1996 set i.e. 37h total (same for all nets).
• Test set is 32 minute subset of hub4 97 eval.
• Noway pruning set to beam 2.0 state_beam 4.0 nhyps 7 prob_min 0.00020

The dimensions varied are:

• Rasta filtering (rasta) vs. plain plp features (plp)
• Per-utterance feature normalization (-norm) vs. no additional normalization
• System used alone (alone) vs. system combined with Gary's best LNA system by averaging the log likelihoods (RNN combo)
• Features alone used (WERR%) vs. features+deltas used (WERR%+deltas). Note that using deltas almost doubles the number of parameters in the net, but the training set size is kept the same.