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egs/wsj/s5/local/run_nnet2.sh
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#!/bin/bash . ./cmd.sh # This shows what you can potentially run; you'd probably want to pick and choose. use_gpu=true if $use_gpu; then local/nnet2/run_5b_gpu.sh # various VTLN combinations, Mel-filterbank features, si284 train (multiplied by 5). local/nnet2/run_5c.sh --use-gpu true # this is on top of fMLLR features. local/nnet2/run_6c_gpu.sh # this is discriminative training of tanh neural nets on top of run_5c_gpu.sh local/nnet2/run_5d.sh --use-gpu true # this is p-norm training on top of fMLLR features. <THIS IS THE MAIN RECIPE> local/nnet2/run_5e_gpu.sh # this is ensemble training of p-norm nnets on top of fMLLR features. local/nnet2/run_6d_gpu.sh # this is discriminative training of p-norm neural nets on top of run_5d_gpu.sh else local/nnet2/run_5b.sh # various VTLN combinations, Mel-filterbank features, si284 train (multiplied by 5). local/nnet2/run_5c.sh --use-gpu false # this is on top of fMLLR features. local/nnet2/run_5d.sh --use-gpu false # this is p-norm on top of fMLLR features. <THIS IS THE MAIN RECIPE> fi |