• kaldi的TIMIT实例二


    ============================================================================
                         MonoPhone Training & Decoding                        
    ============================================================================
    steps/train_mono.sh --nj 30 --cmd run.pl --mem 4G data/train data/lang exp/mono
    steps/train_mono.sh: Initializing monophone system.
    steps/train_mono.sh: Compiling training graphs
    steps/train_mono.sh: Aligning data equally (pass 0)
    steps/train_mono.sh: Pass 1
    steps/train_mono.sh: Aligning data
    steps/train_mono.sh: Pass 2
    steps/train_mono.sh: Aligning data
    ....

    steps/diagnostic/analyze_alignments.sh --cmd run.pl --mem 4G data/lang exp/mono
    steps/diagnostic/analyze_alignments.sh: see stats in exp/mono/log/analyze_alignments.log
    2 warnings in exp/mono/log/align.*.*.log
    exp/mono: nj=30 align prob=-99.15 over 3.12h [retry=0.0%, fail=0.0%] states=144 gauss=986
    steps/train_mono.sh: Done training monophone system in exp/mono

    tree-info exp/mono/tree 
    tree-info exp/mono/tree 
    fsttablecompose data/lang_test_bg/L_disambig.fst data/lang_test_bg/G.fst 
    fstdeterminizestar --use-log=true 
    fstminimizeencoded 
    fstpushspecial 
    fstisstochastic data/lang_test_bg/tmp/LG.fst 
    -0.00841336 -0.00928521
    fstcomposecontext --context-size=1 --central-position=0 --read-disambig-syms=data/lang_test_bg/phones/disambig.int --write-disambig-syms=data/lang_test_bg/tmp/disambig_ilabels_1_0.int data/lang_test_bg/tmp/ilabels_1_0.31072 
    fstisstochastic data/lang_test_bg/tmp/CLG_1_0.fst 
    -0.00841336 -0.00928521
    make-h-transducer --disambig-syms-out=exp/mono/graph/disambig_tid.int --transition-scale=1.0 data/lang_test_bg/tmp/ilabels_1_0 exp/mono/tree exp/mono/final.mdl 
    fstminimizeencoded 
    fstdeterminizestar --use-log=true 
    fsttablecompose exp/mono/graph/Ha.fst data/lang_test_bg/tmp/CLG_1_0.fst 
    fstrmsymbols exp/mono/graph/disambig_tid.int 
    fstrmepslocal 
    fstisstochastic exp/mono/graph/HCLGa.fst 
    0.000381709 -0.00951555
    add-self-loops --self-loop-scale=0.1 --reorder=true exp/mono/final.mdl 
    steps/decode.sh --nj 5 --cmd run.pl --mem 4G exp/mono/graph data/dev exp/mono/decode_dev
    decode.sh: feature type is delta
    steps/diagnostic/analyze_lats.sh --cmd run.pl --mem 4G exp/mono/graph exp/mono/decode_dev
    steps/diagnostic/analyze_lats.sh: see stats in exp/mono/decode_dev/log/analyze_alignments.log
    Overall, lattice depth (10,50,90-percentile)=(5,25,121) and mean=56.0
    steps/diagnostic/analyze_lats.sh: see stats in exp/mono/decode_dev/log/analyze_lattice_depth_stats.log
    steps/decode.sh --nj 5 --cmd run.pl --mem 4G exp/mono/graph data/test exp/mono/decode_test
    decode.sh: feature type is delta
    steps/diagnostic/analyze_lats.sh --cmd run.pl --mem 4G exp/mono/graph exp/mono/decode_test
    steps/diagnostic/analyze_lats.sh: see stats in exp/mono/decode_test/log/analyze_alignments.log
    Overall, lattice depth (10,50,90-percentile)=(6,27,143) and mean=70.8
    steps/diagnostic/analyze_lats.sh: see stats in exp/mono/decode_test/log/analyze_lattice_depth_stats.log
    ============================================================================
               tri1 : Deltas + Delta-Deltas Training & Decoding               
    ============================================================================
    steps/align_si.sh --boost-silence 1.25 --nj 30 --cmd run.pl --mem 4G data/train data/lang exp/mono exp/mono_ali
    steps/align_si.sh: feature type is delta
    steps/align_si.sh: aligning data in data/train using model from exp/mono, putting alignments in exp/mono_ali
    steps/diagnostic/analyze_alignments.sh --cmd run.pl --mem 4G data/lang exp/mono_ali
    steps/diagnostic/analyze_alignments.sh: see stats in exp/mono_ali/log/analyze_alignments.log
    steps/align_si.sh: done aligning data.
    steps/train_deltas.sh --cmd run.pl --mem 4G 2500 15000 data/train data/lang exp/mono_ali exp/tri1
    steps/train_deltas.sh: accumulating tree stats
    steps/train_deltas.sh: getting questions for tree-building, via clustering
    steps/train_deltas.sh: building the tree
    steps/train_deltas.sh: converting alignments from exp/mono_ali to use current tree
    steps/train_deltas.sh: compiling graphs of transcripts
    steps/train_deltas.sh: training pass 1
    steps/train_deltas.sh: training pass 2
    ...

    steps/diagnostic/analyze_alignments.sh --cmd run.pl --mem 4G data/lang exp/tri1
    steps/diagnostic/analyze_alignments.sh: see stats in exp/tri1/log/analyze_alignments.log

    exp/tri1: nj=30 align prob=-95.28 over 3.12h [retry=0.0%, fail=0.0%] states=1893 gauss=15025 tree-impr=5.40
    steps/train_deltas.sh: Done training system with delta+delta-delta features in exp/tri1

    steps/train_deltas.sh: Done training system with delta+delta-delta features in exp/tri1
    tree-info exp/tri1/tree
    tree-info exp/tri1/tree
    fstcomposecontext --context-size=3 --central-position=1 --read-disambig-syms=data/lang_test_bg/phones/disambig.int --write-disambig-syms=data/lang_test_bg/tmp/disambig_ilabels_3_1.int data/lang_test_bg/tmp/ilabels_3_1.28346
    fstisstochastic data/lang_test_bg/tmp/CLG_3_1.fst
    0 -0.00928518
    make-h-transducer --disambig-syms-out=exp/tri1/graph/disambig_tid.int --transition-scale=1.0 data/lang_test_bg/tmp/ilabels_3_1 exp/tri1/tree exp/tri1/final.mdl
    fsttablecompose exp/tri1/graph/Ha.fst data/lang_test_bg/tmp/CLG_3_1.fst
    fstdeterminizestar --use-log=true
    fstrmsymbols exp/tri1/graph/disambig_tid.int
    fstminimizeencoded
    fstrmepslocal
    fstisstochastic exp/tri1/graph/HCLGa.fst
    0.000449687 -0.0175771
    HCLGa is not stochastic
    add-self-loops --self-loop-scale=0.1 --reorder=true exp/tri1/final.mdl
    steps/decode.sh --nj 5 --cmd run.pl --mem 4G exp/tri1/graph data/dev exp/tri1/decode_dev
    decode.sh: feature type is delta
    steps/diagnostic/analyze_lats.sh --cmd run.pl --mem 4G exp/tri1/graph exp/tri1/decode_dev
    steps/diagnostic/analyze_lats.sh: see stats in exp/tri1/decode_dev/log/analyze_alignments.log
    Overall, lattice depth (10,50,90-percentile)=(3,11,41) and mean=19.0
    steps/diagnostic/analyze_lats.sh: see stats in exp/tri1/decode_dev/log/analyze_lattice_depth_stats.log
    steps/decode.sh --nj 5 --cmd run.pl --mem 4G exp/tri1/graph data/test exp/tri1/decode_test
    decode.sh: feature type is delta
    steps/diagnostic/analyze_lats.sh --cmd run.pl --mem 4G exp/tri1/graph exp/tri1/decode_test
    steps/diagnostic/analyze_lats.sh: see stats in exp/tri1/decode_test/log/analyze_alignments.log
    Overall, lattice depth (10,50,90-percentile)=(3,12,47) and mean=21.8
    steps/diagnostic/analyze_lats.sh: see stats in exp/tri1/decode_test/log/analyze_lattice_depth_stats.log

    ============================================================================
                     tri2 : LDA + MLLT Training & Decoding                    
    ============================================================================
    steps/align_si.sh --nj 30 --cmd run.pl --mem 4G data/train data/lang exp/tri1 exp/tri1_ali
    steps/align_si.sh: feature type is delta
    steps/align_si.sh: aligning data in data/train using model from exp/tri1, putting alignments in exp/tri1_ali
    steps/diagnostic/analyze_alignments.sh --cmd run.pl --mem 4G data/lang exp/tri1_ali
    steps/diagnostic/analyze_alignments.sh: see stats in exp/tri1_ali/log/analyze_alignments.log
    steps/align_si.sh: done aligning data.
    steps/train_lda_mllt.sh --cmd run.pl --mem 4G --splice-opts --left-context=3 --right-context=3 2500 15000 data/train data/lang exp/tri1_ali exp/tri2
    steps/train_lda_mllt.sh: Accumulating LDA statistics.
    steps/train_lda_mllt.sh: Accumulating tree stats
    steps/train_lda_mllt.sh: Getting questions for tree clustering.
    steps/train_lda_mllt.sh: Building the tree
    steps/train_lda_mllt.sh: Initializing the model
    steps/train_lda_mllt.sh: Converting alignments from exp/tri1_ali to use current tree
    steps/train_lda_mllt.sh: Compiling graphs of transcripts
    Training pass 1
    Training pass 2
    steps/train_lda_mllt.sh: Estimating MLLT
    Training pass 3
    Training pass 4
    ...

    steps/diagnostic/analyze_alignments.sh --cmd run.pl --mem 4G data/lang exp/tri2
    steps/diagnostic/analyze_alignments.sh: see stats in exp/tri2/log/analyze_alignments.log
    1 warnings in exp/tri2/log/compile_questions.log
    110 warnings in exp/tri2/log/update.*.log
    99 warnings in exp/tri2/log/init_model.log
    exp/tri2: nj=30 align prob=-47.93 over 3.12h [retry=0.0%, fail=0.0%] states=2021 gauss=15026 tree-impr=5.57 lda-sum=28.43 mllt:impr,logdet=1.66,2.28
    steps/train_lda_mllt.sh: Done training system with LDA+MLLT features in exp/tri2
    tree-info exp/tri2/tree
    tree-info exp/tri2/tree
    make-h-transducer --disambig-syms-out=exp/tri2/graph/disambig_tid.int --transition-scale=1.0 data/lang_test_bg/tmp/ilabels_3_1 exp/tri2/tree exp/tri2/final.mdl
    fsttablecompose exp/tri2/graph/Ha.fst data/lang_test_bg/tmp/CLG_3_1.fst
    fstminimizeencoded
    fstdeterminizestar --use-log=true
    fstrmsymbols exp/tri2/graph/disambig_tid.int
    fstrmepslocal
    fstisstochastic exp/tri2/graph/HCLGa.fst
    0.000472258 -0.0175772
    HCLGa is not stochastic
    add-self-loops --self-loop-scale=0.1 --reorder=true exp/tri2/final.mdl
    steps/decode.sh --nj 5 --cmd run.pl --mem 4G exp/tri2/graph data/dev exp/tri2/decode_dev
    decode.sh: feature type is lda
    steps/diagnostic/analyze_lats.sh --cmd run.pl --mem 4G exp/tri2/graph exp/tri2/decode_dev
    steps/diagnostic/analyze_lats.sh: see stats in exp/tri2/decode_dev/log/analyze_alignments.log
    Overall, lattice depth (10,50,90-percentile)=(2,8,29) and mean=13.2
    steps/diagnostic/analyze_lats.sh: see stats in exp/tri2/decode_dev/log/analyze_lattice_depth_stats.log
    steps/decode.sh --nj 5 --cmd run.pl --mem 4G exp/tri2/graph data/test exp/tri2/decode_test
    decode.sh: feature type is lda
    steps/diagnostic/analyze_lats.sh --cmd run.pl --mem 4G exp/tri2/graph exp/tri2/decode_test
    steps/diagnostic/analyze_lats.sh: see stats in exp/tri2/decode_test/log/analyze_alignments.log
    Overall, lattice depth (10,50,90-percentile)=(2,9,33) and mean=14.9
    steps/diagnostic/analyze_lats.sh: see stats in exp/tri2/decode_test/log/analyze_lattice_depth_stats.log

    ============================================================================
                  tri3 : LDA + MLLT + SAT Training & Decoding                 
    ============================================================================
    steps/align_si.sh --nj 30 --cmd run.pl --mem 4G --use-graphs true data/train data/lang exp/tri2 exp/tri2_ali
    steps/align_si.sh: feature type is lda
    steps/align_si.sh: aligning data in data/train using model from exp/tri2, putting alignments in exp/tri2_ali
    steps/diagnostic/analyze_alignments.sh --cmd run.pl --mem 4G data/lang exp/tri2_ali
    steps/diagnostic/analyze_alignments.sh: see stats in exp/tri2_ali/log/analyze_alignments.log
    steps/align_si.sh: done aligning data.
    steps/train_sat.sh --cmd run.pl --mem 4G 2500 15000 data/train data/lang exp/tri2_ali exp/tri3
    steps/train_sat.sh: feature type is lda
    steps/train_sat.sh: obtaining initial fMLLR transforms since not present in exp/tri2_ali
    steps/train_sat.sh: Accumulating tree stats
    steps/train_sat.sh: Getting questions for tree clustering.
    steps/train_sat.sh: Building the tree
    steps/train_sat.sh: Initializing the model
    steps/train_sat.sh: Converting alignments from exp/tri2_ali to use current tree
    steps/train_sat.sh: Compiling graphs of transcripts
    Pass 1
    Pass 2
    Estimating fMLLR transforms
    Pass 3
    Pass 4
    ...

    steps/diagnostic/analyze_alignments.sh --cmd run.pl --mem 4G data/lang exp/tri3
    steps/diagnostic/analyze_alignments.sh: see stats in exp/tri3/log/analyze_alignments.log
    15 warnings in exp/tri3/log/update.*.log
    43 warnings in exp/tri3/log/init_model.log
    1 warnings in exp/tri3/log/compile_questions.log
    steps/train_sat.sh: Likelihood evolution:
    -50.2406 -49.3636 -49.1648 -48.9681 -48.2487 -47.5314 -47.0963 -46.8406 -46.6005 -46.0718 -45.8132 -45.4844 -45.2978 -45.1566 -45.0342 -44.9283 -44.8193 -44.7107 -44.6095 -44.4491 -44.3126 -44.2252 -44.1415 -44.0622 -43.9841 -43.9087 -43.8345 -43.7629 -43.6936 -43.6003 -43.5265 -43.5005 -43.484 -43.4717
    exp/tri3: nj=30 align prob=-47.09 over 3.12h [retry=0.0%, fail=0.0%] states=1920 gauss=15011 fmllr-impr=4.04 over 2.79h tree-impr=8.82
    steps/train_sat.sh: done training SAT system in exp/tri3
    tree-info exp/tri3/tree
    tree-info exp/tri3/tree
    make-h-transducer --disambig-syms-out=exp/tri3/graph/disambig_tid.int --transition-scale=1.0 data/lang_test_bg/tmp/ilabels_3_1 exp/tri3/tree exp/tri3/final.mdl
    fsttablecompose exp/tri3/graph/Ha.fst data/lang_test_bg/tmp/CLG_3_1.fst
    fstrmepslocal
    fstdeterminizestar --use-log=true
    fstrmsymbols exp/tri3/graph/disambig_tid.int
    fstminimizeencoded
    fstisstochastic exp/tri3/graph/HCLGa.fst
    0.000444886 -0.0175772
    HCLGa is not stochastic
    add-self-loops --self-loop-scale=0.1 --reorder=true exp/tri3/final.mdl
    steps/decode_fmllr.sh --nj 5 --cmd run.pl --mem 4G exp/tri3/graph data/dev exp/tri3/decode_dev
    steps/decode.sh --scoring-opts --num-threads 1 --skip-scoring false --acwt 0.083333 --nj 5 --cmd run.pl --mem 4G --beam 10.0 --model exp/tri3/final.alimdl --max-active 2000 exp/tri3/graph data/dev exp/tri3/decode_dev.si
    decode.sh: feature type is lda
    steps/diagnostic/analyze_lats.sh --cmd run.pl --mem 4G exp/tri3/graph exp/tri3/decode_dev.si
    steps/diagnostic/analyze_lats.sh: see stats in exp/tri3/decode_dev.si/log/analyze_alignments.log
    Overall, lattice depth (10,50,90-percentile)=(2,9,34) and mean=15.6

    steps/diagnostic/analyze_lats.sh: see stats in exp/tri3/decode_dev.si/log/analyze_lattice_depth_stats.log
    steps/decode_fmllr.sh: feature type is lda
    steps/decode_fmllr.sh: getting first-pass fMLLR transforms.
    steps/decode_fmllr.sh: doing main lattice generation phase
    steps/decode_fmllr.sh: estimating fMLLR transforms a second time.
    steps/decode_fmllr.sh: doing a final pass of acoustic rescoring.
    steps/diagnostic/analyze_lats.sh --cmd run.pl --mem 4G exp/tri3/graph exp/tri3/decode_dev
    steps/diagnostic/analyze_lats.sh: see stats in exp/tri3/decode_dev/log/analyze_alignments.log
    Overall, lattice depth (10,50,90-percentile)=(1,5,16) and mean=7.7
    steps/diagnostic/analyze_lats.sh: see stats in exp/tri3/decode_dev/log/analyze_lattice_depth_stats.log
    steps/decode_fmllr.sh --nj 5 --cmd run.pl --mem 4G exp/tri3/graph data/test exp/tri3/decode_test
    steps/decode.sh --scoring-opts --num-threads 1 --skip-scoring false --acwt 0.083333 --nj 5 --cmd run.pl --mem 4G --beam 10.0 --model exp/tri3/final.alimdl --max-active 2000 exp/tri3/graph data/test exp/tri3/decode_test.si
    decode.sh: feature type is lda
    steps/diagnostic/analyze_lats.sh --cmd run.pl --mem 4G exp/tri3/graph exp/tri3/decode_test.si
    steps/diagnostic/analyze_lats.sh: see stats in exp/tri3/decode_test.si/log/analyze_alignments.log
    Overall, lattice depth (10,50,90-percentile)=(2,10,37) and mean=16.8
    steps/diagnostic/analyze_lats.sh: see stats in exp/tri3/decode_test.si/log/analyze_lattice_depth_stats.log
    steps/decode_fmllr.sh: feature type is lda
    steps/decode_fmllr.sh: getting first-pass fMLLR transforms.
    steps/decode_fmllr.sh: doing main lattice generation phase
    steps/decode_fmllr.sh: estimating fMLLR transforms a second time.
    steps/decode_fmllr.sh: doing a final pass of acoustic rescoring.
    steps/diagnostic/analyze_lats.sh --cmd run.pl --mem 4G exp/tri3/graph exp/tri3/decode_test
    steps/diagnostic/analyze_lats.sh: see stats in exp/tri3/decode_test/log/analyze_alignments.log
    Overall, lattice depth (10,50,90-percentile)=(1,5,18) and mean=8.6
    steps/diagnostic/analyze_lats.sh: see stats in exp/tri3/decode_test/log/analyze_lattice_depth_stats.log

    ============================================================================
                            SGMM2 Training & Decoding                         
    ============================================================================
    steps/align_fmllr.sh --nj 30 --cmd run.pl --mem 4G data/train data/lang exp/tri3 exp/tri3_ali
    steps/align_fmllr.sh: feature type is lda
    steps/align_fmllr.sh: compiling training graphs
    steps/align_fmllr.sh: aligning data in data/train using exp/tri3/final.alimdl and speaker-independent features.
    steps/align_fmllr.sh: computing fMLLR transforms
    steps/align_fmllr.sh: doing final alignment.
    steps/align_fmllr.sh: done aligning data.
    steps/diagnostic/analyze_alignments.sh --cmd run.pl --mem 4G data/lang exp/tri3_ali
    steps/diagnostic/analyze_alignments.sh: see stats in exp/tri3_ali/log/analyze_alignments.log

    steps/train_ubm.sh --cmd run.pl --mem 4G 400 data/train data/lang exp/tri3_ali exp/ubm4
    steps/train_ubm.sh: feature type is lda
    steps/train_ubm.sh: using transforms from exp/tri3_ali
    steps/train_ubm.sh: clustering model exp/tri3_ali/final.mdl to get initial UBM
    steps/train_ubm.sh: doing Gaussian selection
    Pass 0
    Pass 1
    Pass 2
    steps/train_sgmm2.sh --cmd run.pl --mem 4G 7000 9000 data/train data/lang exp/tri3_ali exp/ubm4/final.ubm exp/sgmm2_4
    steps/train_sgmm2.sh: feature type is lda
    steps/train_sgmm2.sh: using transforms from exp/tri3_ali
    steps/train_sgmm2.sh: accumulating tree stats
    steps/train_sgmm2.sh: Getting questions for tree clustering.
    steps/train_sgmm2.sh: Building the tree
    steps/train_sgmm2.sh: Initializing the model
    steps/train_sgmm2.sh: doing Gaussian selection
    steps/train_sgmm2.sh: compiling training graphs
    steps/train_sgmm2.sh: converting alignments
    steps/train_sgmm2.sh: training pass 0 ...
    steps/train_sgmm2.sh: training pass 1 ...
    steps/train_sgmm2.sh: training pass 2 ...
    steps/train_sgmm2.sh: training pass 3 ...
    steps/train_sgmm2.sh: training pass 4 ...
    steps/train_sgmm2.sh: training pass 5 ...
    steps/train_sgmm2.sh: re-aligning data
    steps/train_sgmm2.sh: training pass 6 ...
    steps/train_sgmm2.sh: training pass 7 ...
    steps/train_sgmm2.sh: training pass 8 ...
    steps/train_sgmm2.sh: training pass 9 ...
    steps/train_sgmm2.sh: training pass 10 ...
    steps/train_sgmm2.sh: re-aligning data
    steps/train_sgmm2.sh: training pass 11 ...
    steps/train_sgmm2.sh: training pass 12 ...
    steps/train_sgmm2.sh: training pass 13 ...
    steps/train_sgmm2.sh: training pass 14 ...
    steps/train_sgmm2.sh: training pass 15 ...
    steps/train_sgmm2.sh: re-aligning data
    steps/train_sgmm2.sh: training pass 16 ...
    steps/train_sgmm2.sh: training pass 17 ...
    steps/train_sgmm2.sh: training pass 18 ...
    steps/train_sgmm2.sh: training pass 19 ...
    steps/train_sgmm2.sh: training pass 20 ...
    steps/train_sgmm2.sh: training pass 21 ...
    steps/train_sgmm2.sh: training pass 22 ...
    steps/train_sgmm2.sh: training pass 23 ...
    steps/train_sgmm2.sh: training pass 24 ...
    steps/train_sgmm2.sh: building alignment model (pass 25)
    steps/train_sgmm2.sh: building alignment model (pass 26)
    steps/train_sgmm2.sh: building alignment model (pass 27)
    198 warnings in exp/sgmm2_4/log/update_ali.*.log
    1723 warnings in exp/sgmm2_4/log/update.*.log
    1 warnings in exp/sgmm2_4/log/compile_questions.log
    Done
    tree-info exp/sgmm2_4/tree
    tree-info exp/sgmm2_4/tree
    make-h-transducer --disambig-syms-out=exp/sgmm2_4/graph/disambig_tid.int --transition-scale=1.0 data/lang_test_bg/tmp/ilabels_3_1 exp/sgmm2_4/tree exp/sgmm2_4/final.mdl
    fsttablecompose exp/sgmm2_4/graph/Ha.fst data/lang_test_bg/tmp/CLG_3_1.fst
    fstrmsymbols exp/sgmm2_4/graph/disambig_tid.int
    fstrmepslocal
    fstdeterminizestar --use-log=true
    fstminimizeencoded
    fstisstochastic exp/sgmm2_4/graph/HCLGa.fst
    0.000485195 -0.0175772
    HCLGa is not stochastic
    add-self-loops --self-loop-scale=0.1 --reorder=true exp/sgmm2_4/final.mdl
    steps/decode_sgmm2.sh --nj 5 --cmd run.pl --mem 4G --transform-dir exp/tri3/decode_dev exp/sgmm2_4/graph data/dev exp/sgmm2_4/decode_dev
    steps/decode_sgmm2.sh: feature type is lda
    steps/decode_sgmm2.sh: using transforms from exp/tri3/decode_dev
    steps/diagnostic/analyze_lats.sh --cmd run.pl --mem 4G exp/sgmm2_4/graph exp/sgmm2_4/decode_dev
    steps/diagnostic/analyze_lats.sh: see stats in exp/sgmm2_4/decode_dev/log/analyze_alignments.log
    Overall, lattice depth (10,50,90-percentile)=(2,6,20) and mean=9.5
    steps/diagnostic/analyze_lats.sh: see stats in exp/sgmm2_4/decode_dev/log/analyze_lattice_depth_stats.log
    steps/decode_sgmm2.sh --nj 5 --cmd run.pl --mem 4G --transform-dir exp/tri3/decode_test exp/sgmm2_4/graph data/test exp/sgmm2_4/decode_test
    steps/decode_sgmm2.sh: feature type is lda
    steps/decode_sgmm2.sh: using transforms from exp/tri3/decode_test
    steps/diagnostic/analyze_lats.sh --cmd run.pl --mem 4G exp/sgmm2_4/graph exp/sgmm2_4/decode_test
    steps/diagnostic/analyze_lats.sh: see stats in exp/sgmm2_4/decode_test/log/analyze_alignments.log
    Overall, lattice depth (10,50,90-percentile)=(2,7,24) and mean=11.0
    steps/diagnostic/analyze_lats.sh: see stats in exp/sgmm2_4/decode_test/log/analyze_lattice_depth_stats.log

  • 相关阅读:
    Beta冲刺——集合随笔
    Beta冲刺——用户调查报告
    Beta冲刺——总结
    Beta冲刺——代码规范、冲刺任务与计划
    Beta冲刺——Day 7
    Beta冲刺——Day 6
    Beta冲刺——Day 5
    Beta冲刺——Day 4
    Beta冲刺——Day3
    beta冲刺汇总
  • 原文地址:https://www.cnblogs.com/welen/p/7525756.html
Copyright © 2020-2023  润新知