跑通kaldi中timit试验以及awk不能找到gensub函数解决方法
2017-11-27 15:45
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我的实验环境是在CentOS 6上,所以各种环境坑等待我去填,建议同学们使用Ubuntu 16.10以上的,或者Debian(我linux入门的第一个操作系统)也好~~~~
继续试验egs/timit例子,发现一个致命问题:
awk(gawk)找不到gensub函数,吸取之前的教训怀疑版本问题:
的确有些年头了,下载最新版本来试试:
wget ftp://ftp.gnu.org/gnu/gawk/gawk-4.2.0.tar.xz
tar xzf gawk-4.2.0.tar.xz
cd gawk-4.2.0
./configure --prefix=/
make & make install
查看新版本:
继续试验egs/timit例子,发现一个致命问题:
awk(gawk)找不到gensub函数,吸取之前的教训怀疑版本问题:
[houwenbin@localhost gawk-4.2.0]$ awk --version awk version 20070501
的确有些年头了,下载最新版本来试试:
wget ftp://ftp.gnu.org/gnu/gawk/gawk-4.2.0.tar.xz
tar xzf gawk-4.2.0.tar.xz
cd gawk-4.2.0
./configure --prefix=/
make & make install
查看新版本:
[houwenbin@localhost ~]$ awk --version GNU Awk 4.2.0, API: 2.0 Copyright (C) 1989, 1991-2017 Free Software Foundation. This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 3 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.[/code]
如果还看不到更新,请检查是否系统中还有awk,比如交叉编译环境NDK下也有awk哦!!!
参照 http://blog.csdn.net/shmilyforyq/article/details/75258259 愉快地开启TIMIT试验了!!![houwenbin@localhost s5]$ ./run.sh ============================================================================ Data & Lexicon & Language Preparation ============================================================================ wav-to-duration --read-entire-file=true scp:train_wav.scp ark,t:train_dur.ark LOG (wav-to-duration[5.2]:main():wav-to-duration.cc:92) Printed duration for 3696 audio files. LOG (wav-to-duration[5.2]:main():wav-to-duration.cc:94) Mean duration was 3.06336, min and max durations were 0.91525, 7.78881 wav-to-duration --read-entire-file=true scp:dev_wav.scp ark,t:dev_dur.ark LOG (wav-to-duration[5.2]:main():wav-to-duration.cc:92) Printed duration for 400 audio files. LOG (wav-to-duration[5.2]:main():wav-to-duration.cc:94) Mean duration was 3.08212, min and max durations were 1.09444, 7.43681 wav-to-duration --read-entire-file=true scp:test_wav.scp ark,t:test_dur.ark LOG (wav-to-duration[5.2]:main():wav-to-duration.cc:92) Printed duration for 192 audio files. LOG (wav-to-duration[5.2]:main():wav-to-duration.cc:94) Mean duration was 3.03646, min and max durations were 1.30562, 6.21444 Data preparation succeeded LOGFILE:/dev/null $bin/ngt -i="$inpfile" -n=$order -gooout=y -o="$gzip -c > $tmpdir/ngram.${sdict}.gz" -fd="$tmpdir/$sdict" $dictionary $additional_parameters >> $logfile 2>&1 $bin/ngt -i="$inpfile" -n=$order -gooout=y -o="$gzip -c > $tmpdir/ngram.${sdict}.gz" -fd="$tmpdir/$sdict" $dictionary $additional_parameters >> $logfile 2>&1 $scr/build-sublm.pl $verbose $prune $prune_thr_str $smoothing "$additional_smoothing_parameters" --size $order --ngrams "$gunzip -c $tmpdir/ngram.${sdict}.gz" -sublm $tmpdir/lm.$sdict $additional_parameters >> $logfile 2>&1 inpfile: data/local/lm_tmp/lm_phone_bg.ilm.gz outfile: /dev/stdout loading up to the LM level 1000 (if any) dub: 10000000 OOV code is 50 OOV code is 50 Saving in txt format to /dev/stdout Dictionary & language model preparation succeeded utils/prepare_lang.sh --sil-prob 0.0 --position-dependent-phones false --num-sil-states 3 data/local/dict sil data/local/lang_tmp data/lang Checking data/local/dict/silence_phones.txt ... --> reading data/local/dict/silence_phones.txt --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces --> data/local/dict/silence_phones.txt is OK Checking data/local/dict/optional_silence.txt ... --> reading data/local/dict/optional_silence.txt --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces --> data/local/dict/optional_silence.txt is OK Checking data/local/dict/nonsilence_phones.txt ... --> reading data/local/dict/nonsilence_phones.txt --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces --> data/local/dict/nonsilence_phones.txt is OK Checking disjoint: silence_phones.txt, nonsilence_phones.txt --> disjoint property is OK. Checking data/local/dict/lexicon.txt --> reading data/local/dict/lexicon.txt --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces --> data/local/dict/lexicon.txt is OK Checking data/local/dict/extra_questions.txt ... --> reading data/local/dict/extra_questions.txt --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces --> data/local/dict/extra_questions.txt is OK --> SUCCESS [validating dictionary directory data/local/dict] **Creating data/local/dict/lexiconp.txt from data/local/dict/lexicon.txt fstaddselfloops data/lang/phones/wdisambig_phones.int data/lang/phones/wdisambig_words.int prepare_lang.sh: validating output directory utils/validate_lang.pl data/lang Checking data/lang/phones.txt ... --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces --> data/lang/phones.txt is OK Checking words.txt: #0 ... --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces --> data/lang/words.txt is OK Checking disjoint: silence.txt, nonsilence.txt, disambig.txt ... --> silence.txt and nonsilence.txt are disjoint --> silence.txt and disambig.txt are disjoint --> disambig.txt and nonsilence.txt are disjoint --> disjoint property is OK Checking sumation: silence.txt, nonsilence.txt, disambig.txt ... --> summation property is OK Checking data/lang/phones/context_indep.{txt, int, csl} ... --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces --> 1 entry/entries in data/lang/phones/context_indep.txt --> data/lang/phones/context_indep.int corresponds to data/lang/phones/context_indep.txt --> data/lang/phones/context_indep.csl corresponds to data/lang/phones/context_indep.txt --> data/lang/phones/context_indep.{txt, int, csl} are OK Checking data/lang/phones/nonsilence.{txt, int, csl} ... --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces --> 47 entry/entries in data/lang/phones/nonsilence.txt --> data/lang/phones/nonsilence.int corresponds to data/lang/phones/nonsilence.txt --> data/lang/phones/nonsilence.csl corresponds to data/lang/phones/nonsilence.txt --> data/lang/phones/nonsilence.{txt, int, csl} are OK Checking data/lang/phones/silence.{txt, int, csl} ... --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces --> 1 entry/entries in data/lang/phones/silence.txt --> data/lang/phones/silence.int corresponds to data/lang/phones/silence.txt --> data/lang/phones/silence.csl corresponds to data/lang/phones/silence.txt --> data/lang/phones/silence.{txt, int, csl} are OK Checking data/lang/phones/optional_silence.{txt, int, csl} ... --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces --> 1 entry/entries in data/lang/phones/optional_silence.txt --> data/lang/phones/optional_silence.int corresponds to data/lang/phones/optional_silence.txt --> data/lang/phones/optional_silence.csl corresponds to data/lang/phones/optional_silence.txt --> data/lang/phones/optional_silence.{txt, int, csl} are OK Checking data/lang/phones/disambig.{txt, int, csl} ... --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces --> 2 entry/entries in data/lang/phones/disambig.txt --> data/lang/phones/disambig.int corresponds to data/lang/phones/disambig.txt --> data/lang/phones/disambig.csl corresponds to data/lang/phones/disambig.txt --> data/lang/phones/disambig.{txt, int, csl} are OK Checking data/lang/phones/roots.{txt, int} ... --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces --> 48 entry/entries in data/lang/phones/roots.txt --> data/lang/phones/roots.int corresponds to data/lang/phones/roots.txt --> data/lang/phones/roots.{txt, int} are OK Checking data/lang/phones/sets.{txt, int} ... --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces --> 48 entry/entries in data/lang/phones/sets.txt --> data/lang/phones/sets.int corresponds to data/lang/phones/sets.txt --> data/lang/phones/sets.{txt, int} are OK Checking data/lang/phones/extra_questions.{txt, int} ... --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces --> 2 entry/entries in data/lang/phones/extra_questions.txt --> data/lang/phones/extra_questions.int corresponds to data/lang/phones/extra_questions.txt --> data/lang/phones/extra_questions.{txt, int} are OK Checking optional_silence.txt ... --> reading data/lang/phones/optional_silence.txt --> data/lang/phones/optional_silence.txt is OK Checking disambiguation symbols: #0 and #1 --> data/lang/phones/disambig.txt has "#0" and "#1" --> data/lang/phones/disambig.txt is OK Checking topo ... Checking word-level disambiguation symbols... --> data/lang/phones/wdisambig.txt exists (newer prepare_lang.sh) Checking data/lang/oov.{txt, int} ... --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces --> 1 entry/entries in data/lang/oov.txt --> data/lang/oov.int corresponds to data/lang/oov.txt --> data/lang/oov.{txt, int} are OK --> data/lang/L.fst is olabel sorted --> data/lang/L_disambig.fst is olabel sorted --> SUCCESS [validating lang directory data/lang] Preparing train, dev and test data Checking data/train/text ... --> reading data/train/text --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces utils/validate_data_dir.sh: Successfully validated data-directory data/train Checking data/dev/text ... --> reading data/dev/text --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces utils/validate_data_dir.sh: Successfully validated data-directory data/dev Checking data/test/text ... --> reading data/test/text --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces utils/validate_data_dir.sh: Successfully validated data-directory data/test Preparing language models for test arpa2fst --disambig-symbol=#0 --read-symbol-table=data/lang_test_bg/words.txt - data/lang_test_bg/G.fst LOG (arpa2fst[5.2]:Read():arpa-file-parser.cc:98) Reading \data\ section. LOG (arpa2fst[5.2]:Read():arpa-file-parser.cc:153) Reading \1-grams: section. LOG (arpa2fst[5.2]:Read():arpa-file-parser.cc:153) Reading \2-grams: section. WARNING (arpa2fst[5.2]:ConsumeNGram():arpa-lm-compiler.cc:313) line 60 [-3.26717 <s> <s>] skipped: n-gram has invalid BOS/EOS placement LOG (arpa2fst[5.2]:RemoveRedundantStates():arpa-lm-compiler.cc:359) Reduced num-states from 50 to 50 fstisstochastic data/lang_test_bg/G.fst 0.000510126 -0.0763018 utils/validate_lang.pl data/lang_test_bg Checking data/lang_test_bg/phones.txt ... --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces --> data/lang_test_bg/phones.txt is OK Checking words.txt: #0 ... --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces --> data/lang_test_bg/words.txt is OK Checking disjoint: silence.txt, nonsilence.txt, disambig.txt ... --> silence.txt and nonsilence.txt are disjoint --> silence.txt and disambig.txt are disjoint --> disambig.txt and nonsilence.txt are disjoint --> disjoint property is OK Checking sumation: silence.txt, nonsilence.txt, disambig.txt ... --> summation property is OK Checking data/lang_test_bg/phones/context_indep.{txt, int, csl} ... --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces --> 1 entry/entries in data/lang_test_bg/phones/context_indep.txt --> data/lang_test_bg/phones/context_indep.int corresponds to data/lang_test_bg/phones/context_indep.txt --> data/lang_test_bg/phones/context_indep.csl corresponds to data/lang_test_bg/phones/context_indep.txt --> data/lang_test_bg/phones/context_indep.{txt, int, csl} are OK Checking data/lang_test_bg/phones/nonsilence.{txt, int, csl} ... --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces --> 47 entry/entries in data/lang_test_bg/phones/nonsilence.txt --> data/lang_test_bg/phones/nonsilence.int corresponds to data/lang_test_bg/phones/nonsilence.txt --> data/lang_test_bg/phones/nonsilence.csl corresponds to data/lang_test_bg/phones/nonsilence.txt --> data/lang_test_bg/phones/nonsilence.{txt, int, csl} are OK Checking data/lang_test_bg/phones/silence.{txt, int, csl} ... --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces --> 1 entry/entries in data/lang_test_bg/phones/silence.txt --> data/lang_test_bg/phones/silence.int corresponds to data/lang_test_bg/phones/silence.txt --> data/lang_test_bg/phones/silence.csl corresponds to data/lang_test_bg/phones/silence.txt --> data/lang_test_bg/phones/silence.{txt, int, csl} are OK Checking data/lang_test_bg/phones/optional_silence.{txt, int, csl} ... --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces --> 1 entry/entries in data/lang_test_bg/phones/optional_silence.txt --> data/lang_test_bg/phones/optional_silence.int corresponds to data/lang_test_bg/phones/optional_silence.txt --> data/lang_test_bg/phones/optional_silence.csl corresponds to data/lang_test_bg/phones/optional_silence.txt --> data/lang_test_bg/phones/optional_silence.{txt, int, csl} are OK Checking data/lang_test_bg/phones/disambig.{txt, int, csl} ... --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces --> 2 entry/entries in data/lang_test_bg/phones/disambig.txt --> data/lang_test_bg/phones/disambig.int corresponds to data/lang_test_bg/phones/disambig.txt --> data/lang_test_bg/phones/disambig.csl corresponds to data/lang_test_bg/phones/disambig.txt --> data/lang_test_bg/phones/disambig.{txt, int, csl} are OK Checking data/lang_test_bg/phones/roots.{txt, int} ... --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces --> 48 entry/entries in data/lang_test_bg/phones/roots.txt --> data/lang_test_bg/phones/roots.int corresponds to data/lang_test_bg/phones/roots.txt --> data/lang_test_bg/phones/roots.{txt, int} are OK Checking data/lang_test_bg/phones/sets.{txt, int} ... --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces --> 48 entry/entries in data/lang_test_bg/phones/sets.txt --> data/lang_test_bg/phones/sets.int corresponds to data/lang_test_bg/phones/sets.txt --> data/lang_test_bg/phones/sets.{txt, int} are OK Checking data/lang_test_bg/phones/extra_questions.{txt, int} ... --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces --> 2 entry/entries in data/lang_test_bg/phones/extra_questions.txt --> data/lang_test_bg/phones/extra_questions.int corresponds to data/lang_test_bg/phones/extra_questions.txt --> data/lang_test_bg/phones/extra_questions.{txt, int} are OK Checking optional_silence.txt ... --> reading data/lang_test_bg/phones/optional_silence.txt --> data/lang_test_bg/phones/optional_silence.txt is OK Checking disambiguation symbols: #0 and #1 --> data/lang_test_bg/phones/disambig.txt has "#0" and "#1" --> data/lang_test_bg/phones/disambig.txt is OK Checking topo ... Checking word-level disambiguation symbols... --> data/lang_test_bg/phones/wdisambig.txt exists (newer prepare_lang.sh) Checking data/lang_test_bg/oov.{txt, int} ... --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces --> 1 entry/entries in data/lang_test_bg/oov.txt --> data/lang_test_bg/oov.int corresponds to data/lang_test_bg/oov.txt --> data/lang_test_bg/oov.{txt, int} are OK --> data/lang_test_bg/L.fst is olabel sorted --> data/lang_test_bg/L_disambig.fst is olabel sorted --> data/lang_test_bg/G.fst is ilabel sorted --> data/lang_test_bg/G.fst has 50 states fstdeterminizestar data/lang_test_bg/G.fst /dev/null --> data/lang_test_bg/G.fst is determinizable --> utils/lang/check_g_properties.pl successfully validated data/lang_test_bg/G.fst --> utils/lang/check_g_properties.pl succeeded. --> Testing determinizability of L_disambig . G fsttablecompose data/lang_test_bg/L_disambig.fst data/lang_test_bg/G.fst fstdeterminizestar --> L_disambig . G is determinizable --> SUCCESS [validating lang directory data/lang_test_bg] Succeeded in formatting data. ============================================================================ MFCC Feature Extration & CMVN for Training and Test set ============================================================================ steps/make_mfcc.sh --cmd run.pl --max-jobs-run 10 --nj 10 data/train exp/make_mfcc/train mfcc Checking data/train/text ... --> reading data/train/text --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces utils/validate_data_dir.sh: Successfully validated data-directory data/train steps/make_mfcc.sh: [info]: no segments file exists: assuming wav.scp indexed by utterance. Succeeded creating MFCC features for train steps/compute_cmvn_stats.sh data/train exp/make_mfcc/train mfcc Succeeded creating CMVN stats for train steps/make_mfcc.sh --cmd run.pl --max-jobs-run 10 --nj 10 data/dev exp/make_mfcc/dev mfcc Checking data/dev/text ... --> reading data/dev/text --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces utils/validate_data_dir.sh: Successfully validated data-directory data/dev steps/make_mfcc.sh: [info]: no segments file exists: assuming wav.scp indexed by utterance. Succeeded creating MFCC features for dev steps/compute_cmvn_stats.sh data/dev exp/make_mfcc/dev mfcc Succeeded creating CMVN stats for dev steps/make_mfcc.sh --cmd run.pl --max-jobs-run 10 --nj 10 data/test exp/make_mfcc/test mfcc Checking data/test/text ... --> reading data/test/text --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces utils/validate_data_dir.sh: Successfully validated data-directory data/test steps/make_mfcc.sh: [info]: no segments file exists: assuming wav.scp indexed by utterance. Succeeded creating MFCC features for test steps/compute_cmvn_stats.sh data/test exp/make_mfcc/test mfcc Succeeded creating CMVN stats for test ============================================================================ MonoPhone Training & Decoding ============================================================================ steps/train_mono.sh --nj 30 --cmd run.pl --max-jobs-run 10 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/train_mono.sh: Pass 3 steps/train_mono.sh: Aligning data steps/train_mono.sh: Pass 4 steps/train_mono.sh: Aligning data steps/train_mono.sh: Pass 5 steps/train_mono.sh: Aligning data steps/train_mono.sh: Pass 6 steps/train_mono.sh: Aligning data steps/train_mono.sh: Pass 7 steps/train_mono.sh: Aligning data steps/train_mono.sh: Pass 8 steps/train_mono.sh: Aligning data steps/train_mono.sh: Pass 9 steps/train_mono.sh: Aligning data steps/train_mono.sh: Pass 10 steps/train_mono.sh: Aligning data steps/train_mono.sh: Pass 11 steps/train_mono.sh: Pass 12 steps/train_mono.sh: Aligning data steps/train_mono.sh: Pass 13 steps/train_mono.sh: Pass 14 steps/train_mono.sh: Aligning data steps/train_mono.sh: Pass 15 steps/train_mono.sh: Pass 16 steps/train_mono.sh: Aligning data steps/train_mono.sh: Pass 17 steps/train_mono.sh: Pass 18 steps/train_mono.sh: Aligning data steps/train_mono.sh: Pass 19 steps/train_mono.sh: Pass 20 steps/train_mono.sh: Aligning data steps/train_mono.sh: Pass 21 steps/train_mono.sh: Pass 22 steps/train_mono.sh: Pass 23 steps/train_mono.sh: Aligning data steps/train_mono.sh: Pass 24 steps/train_mono.sh: Pass 25 steps/train_mono.sh: Pass 26 steps/train_mono.sh: Aligning data steps/train_mono.sh: Pass 27 steps/train_mono.sh: Pass 28 steps/train_mono.sh: Pass 29 steps/train_mono.sh: Aligning data steps/train_mono.sh: Pass 30 steps/train_mono.sh: Pass 31 steps/train_mono.sh: Pass 32 steps/train_mono.sh: Aligning data steps/train_mono.sh: Pass 33 steps/train_mono.sh: Pass 34 steps/train_mono.sh: Pass 35 steps/train_mono.sh: Aligning data steps/train_mono.sh: Pass 36 steps/train_mono.sh: Pass 37 steps/train_mono.sh: Pass 38 steps/train_mono.sh: Aligning data steps/train_mono.sh: Pass 39 steps/diagnostic/analyze_alignments.sh --cmd run.pl --max-jobs-run 10 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 fstpushspecial fstminimizeencoded 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_0.9606 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 fsttablecompose exp/mono/graph/Ha.fst data/lang_test_bg/tmp/CLG_1_0.fst fstminimizeencoded fstdeterminizestar --use-log=true 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 --max-jobs-run 10 exp/mono/graph data/dev exp/mono/decode_dev decode.sh: feature type is delta steps/diagnostic/analyze_lats.sh --cmd run.pl --max-jobs-run 10 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)=(5,25,120) and mean=55.6 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 --max-jobs-run 10 exp/mono/graph data/test exp/mono/decode_test decode.sh: feature type is delta steps/diagnostic/analyze_lats.sh --cmd run.pl --max-jobs-run 10 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=74.1 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 --max-jobs-run 10 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 --max-jobs-run 10 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 --max-jobs-run 10 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/train_deltas.sh: training pass 3 steps/train_deltas.sh: training pass 4 steps/train_deltas.sh: training pass 5 steps/train_deltas.sh: training pass 6 steps/train_deltas.sh: training pass 7 steps/train_deltas.sh: training pass 8 steps/train_deltas.sh: training pass 9 steps/train_deltas.sh: training pass 10 steps/train_deltas.sh: aligning data steps/train_deltas.sh: training pass 11 steps/train_deltas.sh: training pass 12 steps/train_deltas.sh: training pass 13 steps/train_deltas.sh: training pass 14 steps/train_deltas.sh: training pass 15 steps/train_deltas.sh: training pass 16 steps/train_deltas.sh: training pass 17 steps/train_deltas.sh: training pass 18 steps/train_deltas.sh: training pass 19 steps/train_deltas.sh: training pass 20 steps/train_deltas.sh: aligning data steps/train_deltas.sh: training pass 21 steps/train_deltas.sh: training pass 22 steps/train_deltas.sh: training pass 23 steps/train_deltas.sh: training pass 24 steps/train_deltas.sh: training pass 25 steps/train_deltas.sh: training pass 26 steps/train_deltas.sh: training pass 27 steps/train_deltas.sh: training pass 28 steps/train_deltas.sh: training pass 29 steps/train_deltas.sh: training pass 30 steps/train_deltas.sh: aligning data steps/train_deltas.sh: training pass 31 steps/train_deltas.sh: training pass 32 steps/train_deltas.sh: training pass 33 steps/train_deltas.sh: training pass 34 steps/diagnostic/analyze_alignments.sh --cmd run.pl --max-jobs-run 10 data/lang exp/tri1 steps/diagnostic/analyze_alignments.sh: see stats in exp/tri1/log/analyze_alignments.log 1 warnings in exp/tri1/log/compile_questions.log 74 warnings in exp/tri1/log/init_model.log 52 warnings in exp/tri1/log/update.*.log exp/tri1: nj=30 align prob=-95.28 over 3.12h [retry=0.0%, fail=0.0%] states=1882 gauss=15036 tree-impr=5.40 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_1.3514 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 fstrmepslocal fsttablecompose exp/tri1/graph/Ha.fst data/lang_test_bg/tmp/CLG_3_1.fst fstrmsymbols exp/tri1/graph/disambig_tid.int fstdeterminizestar --use-log=true fstminimizeencoded fstisstochastic exp/tri1/graph/HCLGa.fst 0.000449687 -0.0175772 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 --max-jobs-run 10 exp/tri1/graph data/dev exp/tri1/decode_dev decode.sh: feature type is delta steps/diagnostic/analyze_lats.sh --cmd run.pl --max-jobs-run 10 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)=(3,11,42) and mean=19.2 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 --max-jobs-run 10 exp/tri1/graph data/test exp/tri1/decode_test decode.sh: feature type is delta steps/diagnostic/analyze_lats.sh --cmd run.pl --max-jobs-run 10 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)=(3,12,49) and mean=21.9 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 --max-jobs-run 10 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 --max-jobs-run 10 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 --max-jobs-run 10 --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/train_lda_mllt.sh: Estimating MLLT Training pass 5 Training pass 6 steps/train_lda_mllt.sh: Estimating MLLT Training pass 7 Training pass 8 Training pass 9 Training pass 10 Aligning data Training pass 11 Training pass 12 steps/train_lda_mllt.sh: Estimating MLLT Training pass 13 Training pass 14 Training pass 15 Training pass 16 Training pass 17 Training pass 18 Training pass 19 Training pass 20 Aligning data Training pass 21 Training pass 22 Training pass 23 Training pass 24 Training pass 25 Training pass 26 Training pass 27 Training pass 28 Training pass 29 Training pass 30 Aligning data Training pass 31 Training pass 32 Training pass 33 Training pass 34 steps/diagnostic/analyze_alignments.sh --cmd run.pl --max-jobs-run 10 data/lang exp/tri2 steps/diagnostic/analyze_alignments.sh: see stats in exp/tri2/log/analyze_alignments.log 183 warnings in exp/tri2/log/update.*.log 105 warnings in exp/tri2/log/init_model.log 1 warnings in exp/tri2/log/compile_questions.log exp/tri2: nj=30 align prob=-47.86 over 3.12h [retry=0.0%, fail=0.0%] states=2010 gauss=15034 tree-impr=5.56 lda-sum=28.46 mllt:impr,logdet=1.63,2.18 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 fstrmepslocal fsttablecompose exp/tri2/graph/Ha.fst data/lang_test_bg/tmp/CLG_3_1.fst fstrmsymbols exp/tri2/graph/disambig_tid.int fstdeterminizestar --use-log=true fstminimizeencoded fstisstochastic exp/tri2/graph/HCLGa.fst 0.000461769 -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 --max-jobs-run 10 exp/tri2/graph data/dev exp/tri2/decode_dev decode.sh: feature type is lda steps/diagnostic/analyze_lats.sh --cmd run.pl --max-jobs-run 10 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=13.3 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 --max-jobs-run 10 exp/tri2/graph data/test exp/tri2/decode_test decode.sh: feature type is lda steps/diagnostic/analyze_lats.sh --cmd run.pl --max-jobs-run 10 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)=(2,8,32) and mean=14.6 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 --max-jobs-run 10 --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 --max-jobs-run 10 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 --max-jobs-run 10 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 Estimating fMLLR transforms Pass 5 Pass 6 Estimating fMLLR transforms Pass 7 Pass 8 Pass 9 Pass 10 Aligning data Pass 11 Pass 12 Estimating fMLLR transforms Pass 13 Pass 14 Pass 15 Pass 16 Pass 17 Pass 18 Pass 19 Pass 20 Aligning data Pass 21 Pass 22 Pass 23 Pass 24 Pass 25 Pass 26 Pass 27 Pass 28 Pass 29 Pass 30 Aligning data Pass 31 Pass 32 Pass 33 Pass 34 steps/diagnostic/analyze_alignments.sh --cmd run.pl --max-jobs-run 10 data/lang exp/tri3 steps/diagnostic/analyze_alignments.sh: see stats in exp/tri3/log/analyze_alignments.log 42 warnings in exp/tri3/log/init_model.log 1 warnings in exp/tri3/log/compile_questions.log 18 warnings in exp/tri3/log/update.*.log steps/train_sat.sh: Likelihood evolution: -50.1573 -49.2762 -49.0764 -48.8736 -48.1773 -47.467 -47.0375 -46.7895 -46.553 -46.0244 -45.767 -45.4404 -45.2512 -45.1163 -45.0002 -44.8829 -44.7724 -44.6672 -44.5614 -44.4011 -44.2651 -44.1746 -44.0909 -44.0093 -43.9307 -43.8546 -43.7783 -43.7032 -43.6313 -43.5378 -43.4676 -43.4394 -43.4229 -43.4139 exp/tri3: nj=30 align prob=-47.01 over 3.12h [retry=0.0%, fail=0.0%] states=1935 gauss=15013 fmllr-impr=4.04 over 2.79h tree-impr=8.71 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 fstrmepslocal fsttablecompose exp/tri3/graph/Ha.fst data/lang_test_bg/tmp/CLG_3_1.fst fstrmsymbols exp/tri3/graph/disambig_tid.int fstdeterminizestar --use-log=true fstminimizeencoded fstisstochastic exp/tri3/graph/HCLGa.fst 0.000461769 -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 --max-jobs-run 10 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 --max-jobs-run 10 --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 --max-jobs-run 10 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=15.2 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 --max-jobs-run 10 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=7.6 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 --max-jobs-run 10 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 --max-jobs-run 10 --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 --max-jobs-run 10 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 --max-jobs-run 10 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)=(1,5,19) 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 --max-jobs-run 10 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 --max-jobs-run 10 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 --max-jobs-run 10 400 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 --max-jobs-run 10 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) 1 warnings in exp/sgmm2_4/log/compile_questions.log 198 warnings in exp/sgmm2_4/log/update_ali.*.log 1726 warnings in exp/sgmm2_4/log/update.*.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 fstrmepslocal fsttablecompose exp/sgmm2_4/graph/Ha.fst data/lang_test_bg/tmp/CLG_3_1.fst fstrmsymbols exp/sgmm2_4/graph/disambig_tid.int fstdeterminizestar --use-log=true fstminimizeencoded fstisstochastic exp/sgmm2_4/graph/HCLGa.fst 0.000476187 -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 --max-jobs-run 10 --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 --max-jobs-run 10 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 --max-jobs-run 10 --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 --max-jobs-run 10 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)=(2,6,23) and mean=10.7 steps/diagnostic/analyze_lats.sh: see stats in exp/sgmm2_4/decode_test/log/analyze_lattice_depth_stats.log ============================================================================ MMI + SGMM2 Training & Decoding ============================================================================ steps/align_sgmm2.sh --nj 30 --cmd run.pl --max-jobs-run 10 --transform-dir exp/tri3_ali --use-graphs true --use-gselect true data/train data/lang exp/sgmm2_4 exp/sgmm2_4_ali steps/align_sgmm2.sh: feature type is lda steps/align_sgmm2.sh: using transforms from exp/tri3_ali steps/align_sgmm2.sh: aligning data in data/train using model exp/sgmm2_4/final.alimdl steps/align_sgmm2.sh: computing speaker vectors (1st pass) steps/align_sgmm2.sh: computing speaker vectors (2nd pass) steps/align_sgmm2.sh: doing final alignment. steps/align_sgmm2.sh: done aligning data. steps/diagnostic/analyze_alignments.sh --cmd run.pl --max-jobs-run 10 data/lang exp/sgmm2_4_ali steps/diagnostic/analyze_alignments.sh: see stats in exp/sgmm2_4_ali/log/analyze_alignments.log steps/make_denlats_sgmm2.sh --nj 30 --sub-split 30 --acwt 0.2 --lattice-beam 10.0 --beam 18.0 --cmd run.pl --max-jobs-run 10 --transform-dir exp/tri3_ali data/train data/lang exp/sgmm2_4_ali exp/sgmm2_4_denlats steps/make_denlats_sgmm2.sh: Making unigram grammar FST in exp/sgmm2_4_denlats/lang steps/make_denlats_sgmm2.sh: Compiling decoding graph in exp/sgmm2_4_denlats/dengraph tree-info exp/sgmm2_4_ali/tree tree-info exp/sgmm2_4_ali/tree fsttablecompose exp/sgmm2_4_denlats/lang/L_disambig.fst exp/sgmm2_4_denlats/lang/G.fst fstminimizeencoded fstdeterminizestar --use-log=true fstpushspecial fstisstochastic exp/sgmm2_4_denlats/lang/tmp/LG.fst 1.27271e-05 1.27271e-05 fstcomposecontext --context-size=3 --central-position=1 --read-disambig-syms=exp/sgmm2_4_denlats/lang/phones/disambig.int --write-disambig-syms=exp/sgmm2_4_denlats/lang/tmp/disambig_ilabels_3_1.int exp/sgmm2_4_denlats/lang/tmp/ilabels_3_1.27913 fstisstochastic exp/sgmm2_4_denlats/lang/tmp/CLG_3_1.fst 1.27657e-05 0 make-h-transducer --disambig-syms-out=exp/sgmm2_4_denlats/dengraph/disambig_tid.int --transition-scale=1.0 exp/sgmm2_4_denlats/lang/tmp/ilabels_3_1 exp/sgmm2_4_ali/tree exp/sgmm2_4_ali/final.mdl fsttablecompose exp/sgmm2_4_denlats/dengraph/Ha.fst exp/sgmm2_4_denlats/lang/tmp/CLG_3_1.fst fstminimizeencoded fstrmepslocal fstrmsymbols exp/sgmm2_4_denlats/dengraph/disambig_tid.int fstdeterminizestar --use-log=true fstisstochastic exp/sgmm2_4_denlats/dengraph/HCLGa.fst 0.000481185 -0.000485819 add-self-loops --self-loop-scale=0.1 --reorder=true exp/sgmm2_4_ali/final.mdl steps/make_denlats_sgmm2.sh: feature type is lda steps/make_denlats_sgmm2.sh: using fMLLR transforms from exp/tri3_ali steps/make_denlats_sgmm2.sh: Merging archives for data subset 1 steps/make_denlats_sgmm2.sh: Merging archives for data subset 2 steps/make_denlats_sgmm2.sh: Merging archives for data subset 3 steps/make_denlats_sgmm2.sh: Merging archives for data subset 4 steps/make_denlats_sgmm2.sh: Merging archives for data subset 5 steps/make_denlats_sgmm2.sh: Merging archives for data subset 6 steps/make_denlats_sgmm2.sh: Merging archives for data subset 7 steps/make_denlats_sgmm2.sh: Merging archives for data subset 8 steps/make_denlats_sgmm2.sh: Merging archives for data subset 9 steps/make_denlats_sgmm2.sh: Merging archives for data subset 10 steps/make_denlats_sgmm2.sh: Merging archives for data subset 11 steps/make_denlats_sgmm2.sh: Merging archives for data subset 12 steps/make_denlats_sgmm2.sh: Merging archives for data subset 13 steps/make_denlats_sgmm2.sh: Merging archives for data subset 14 steps/make_denlats_sgmm2.sh: Merging archives for data subset 15 steps/make_denlats_sgmm2.sh: Merging archives for data subset 16 steps/make_denlats_sgmm2.sh: Merging archives for data subset 17 steps/make_denlats_sgmm2.sh: Merging archives for data subset 18 steps/make_denlats_sgmm2.sh: Merging archives for data subset 19 steps/make_denlats_sgmm2.sh: Merging archives for data subset 20 steps/make_denlats_sgmm2.sh: Merging archives for data subset 21 steps/make_denlats_sgmm2.sh: Merging archives for data subset 22 steps/make_denlats_sgmm2.sh: Merging archives for data subset 23 steps/make_denlats_sgmm2.sh: Merging archives for data subset 24 steps/make_denlats_sgmm2.sh: Merging archives for data subset 25 steps/make_denlats_sgmm2.sh: Merging archives for data subset 26 steps/make_denlats_sgmm2.sh: Merging archives for data subset 27 steps/make_denlats_sgmm2.sh: Merging archives for data subset 28 steps/make_denlats_sgmm2.sh: Merging archives for data subset 29 steps/make_denlats_sgmm2.sh: Merging archives for data subset 30 steps/make_denlats_sgmm2.sh: done generating denominator lattices with SGMMs. steps/train_mmi_sgmm2.sh --acwt 0.2 --cmd run.pl --max-jobs-run 10 --transform-dir exp/tri3_ali --boost 0.1 --drop-frames true data/train data/lang exp/sgmm2_4_ali exp/sgmm2_4_denlats exp/sgmm2_4_mmi_b0.1 steps/train_mmi_sgmm2.sh: feature type is lda steps/train_mmi_sgmm2.sh: using transforms from exp/tri3_ali steps/train_mmi_sgmm2.sh: using speaker vectors from exp/sgmm2_4_ali steps/train_mmi_sgmm2.sh: using Gaussian-selection info from exp/sgmm2_4_ali Iteration 0 of MMI training Iteration 0: objf was 0.500664422464595, MMI auxf change was 0.0161997754313345 Iteration 1 of MMI training Iteration 1: objf was 0.515510864906709, MMI auxf change was 0.00240651195788137 Iteration 2 of MMI training Iteration 2: objf was 0.518162614976294, MMI auxf change was 0.000690078350104861 Iteration 3 of MMI training Iteration 3: objf was 0.519018203153884, MMI auxf change was 0.000602987314448584 MMI training finished steps/decode_sgmm2_rescore.sh --cmd run.pl --max-jobs-run 10 --iter 1 --transform-dir exp/tri3/decode_dev data/lang_test_bg data/dev exp/sgmm2_4/decode_dev exp/sgmm2_4_mmi_b0.1/decode_dev_it1 steps/decode_sgmm2_rescore.sh: using speaker vectors from exp/sgmm2_4/decode_dev steps/decode_sgmm2_rescore.sh: feature type is lda steps/decode_sgmm2_rescore.sh: using transforms from exp/tri3/decode_dev steps/decode_sgmm2_rescore.sh: rescoring lattices with SGMM model in exp/sgmm2_4_mmi_b0.1/1.mdl steps/decode_sgmm2_rescore.sh --cmd run.pl --max-jobs-run 10 --iter 1 --transform-dir exp/tri3/decode_test data/lang_test_bg data/test exp/sgmm2_4/decode_test exp/sgmm2_4_mmi_b0.1/decode_test_it1 steps/decode_sgmm2_rescore.sh: using speaker vectors from exp/sgmm2_4/decode_test steps/decode_sgmm2_rescore.sh: feature type is lda steps/decode_sgmm2_rescore.sh: using transforms from exp/tri3/decode_test steps/decode_sgmm2_rescore.sh: rescoring lattices with SGMM model in exp/sgmm2_4_mmi_b0.1/1.mdl steps/decode_sgmm2_rescore.sh --cmd run.pl --max-jobs-run 10 --iter 2 --transform-dir exp/tri3/decode_dev data/lang_test_bg data/dev exp/sgmm2_4/decode_dev exp/sgmm2_4_mmi_b0.1/decode_dev_it2 steps/decode_sgmm2_rescore.sh: using speaker vectors from exp/sgmm2_4/decode_dev steps/decode_sgmm2_rescore.sh: feature type is lda steps/decode_sgmm2_rescore.sh: using transforms from exp/tri3/decode_dev steps/decode_sgmm2_rescore.sh: rescoring lattices with SGMM model in exp/sgmm2_4_mmi_b0.1/2.mdl steps/decode_sgmm2_rescore.sh --cmd run.pl --max-jobs-run 10 --iter 2 --transform-dir exp/tri3/decode_test data/lang_test_bg data/test exp/sgmm2_4/decode_test exp/sgmm2_4_mmi_b0.1/decode_test_it2 steps/decode_sgmm2_rescore.sh: using speaker vectors from exp/sgmm2_4/decode_test steps/decode_sgmm2_rescore.sh: feature type is lda steps/decode_sgmm2_rescore.sh: using transforms from exp/tri3/decode_test steps/decode_sgmm2_rescore.sh: rescoring lattices with SGMM model in exp/sgmm2_4_mmi_b0.1/2.mdl steps/decode_sgmm2_rescore.sh --cmd run.pl --max-jobs-run 10 --iter 3 --transform-dir exp/tri3/decode_dev data/lang_test_bg data/dev exp/sgmm2_4/decode_dev exp/sgmm2_4_mmi_b0.1/decode_dev_it3 steps/decode_sgmm2_rescore.sh: using speaker vectors from exp/sgmm2_4/decode_dev steps/decode_sgmm2_rescore.sh: feature type is lda steps/decode_sgmm2_rescore.sh: using transforms from exp/tri3/decode_dev steps/decode_sgmm2_rescore.sh: rescoring lattices with SGMM model in exp/sgmm2_4_mmi_b0.1/3.mdl steps/decode_sgmm2_rescore.sh --cmd run.pl --max-jobs-run 10 --iter 3 --transform-dir exp/tri3/decode_test data/lang_test_bg data/test exp/sgmm2_4/decode_test exp/sgmm2_4_mmi_b0.1/decode_test_it3 steps/decode_sgmm2_rescore.sh: using speaker vectors from exp/sgmm2_4/decode_test steps/decode_sgmm2_rescore.sh: feature type is lda steps/decode_sgmm2_rescore.sh: using transforms from exp/tri3/decode_test steps/decode_sgmm2_rescore.sh: rescoring lattices with SGMM model in exp/sgmm2_4_mmi_b0.1/3.mdl steps/decode_sgmm2_rescore.sh --cmd run.pl --max-jobs-run 10 --iter 4 --transform-dir exp/tri3/decode_dev data/lang_test_bg data/dev exp/sgmm2_4/decode_dev exp/sgmm2_4_mmi_b0.1/decode_dev_it4 steps/decode_sgmm2_rescore.sh: using speaker vectors from exp/sgmm2_4/decode_dev steps/decode_sgmm2_rescore.sh: feature type is lda steps/decode_sgmm2_rescore.sh: using transforms from exp/tri3/decode_dev steps/decode_sgmm2_rescore.sh: rescoring lattices with SGMM model in exp/sgmm2_4_mmi_b0.1/4.mdl steps/decode_sgmm2_rescore.sh --cmd run.pl --max-jobs-run 10 --iter 4 --transform-dir exp/tri3/decode_test data/lang_test_bg data/test exp/sgmm2_4/decode_test exp/sgmm2_4_mmi_b0.1/decode_test_it4 steps/decode_sgmm2_rescore.sh: using speaker vectors from exp/sgmm2_4/decode_test steps/decode_sgmm2_rescore.sh: feature type is lda steps/decode_sgmm2_rescore.sh: using transforms from exp/tri3/decode_test steps/decode_sgmm2_rescore.sh: rescoring lattices with SGMM model in exp/sgmm2_4_mmi_b0.1/4.mdl ============================================================================ DNN Hybrid Training & Decoding ============================================================================ steps/nnet2/train_tanh.sh --mix-up 5000 --initial-learning-rate 0.015 --final-learning-rate 0.002 --num-hidden-layers 2 --num-jobs-nnet 30 --cmd run.pl --max-jobs-run 10 data/train data/lang exp/tri3_ali exp/tri4_nnet steps/nnet2/train_tanh.sh: calling get_lda.sh steps/nnet2/get_lda.sh --transform-dir exp/tri3_ali --splice-width 4 --cmd run.pl --max-jobs-run 10 data/train data/lang exp/tri3_ali exp/tri4_nnet steps/nnet2/get_lda.sh: feature type is lda steps/nnet2/get_lda.sh: using transforms from exp/tri3_ali feat-to-dim 'ark,s,cs:utils/subset_scp.pl --quiet 333 data/train/split30/1/feats.scp | apply-cmvn --utt2spk=ark:data/train/split30/1/utt2spk scp:data/train/split30/1/cmvn.scp scp:- ark:- | splice-feats --left-context=3 --right-context=3 ark:- ark:- | transform-feats exp/tri4_nnet/final.mat ark:- ark:- | transform-feats --utt2spk=ark:data/train/split30/1/utt2spk ark:exp/tri3_ali/trans.1 ark:- ark:- |' - transform-feats exp/tri4_nnet/final.mat ark:- ark:- splice-feats --left-context=3 --right-context=3 ark:- ark:- apply-cmvn --utt2spk=ark:data/train/split30/1/utt2spk scp:data/train/split30/1/cmvn.scp scp:- ark:- transform-feats --utt2spk=ark:data/train/split30/1/utt2spk ark:exp/tri3_ali/trans.1 ark:- ark:- WARNING (feat-to-dim[5.2]:Close():kaldi-io.cc:501) Pipe utils/subset_scp.pl --quiet 333 data/train/split30/1/feats.scp | apply-cmvn --utt2spk=ark:data/train/split30/1/utt2spk scp:data/train/split30/1/cmvn.scp scp:- ark:- | splice-feats --left-context=3 --right-context=3 ark:- ark:- | transform-feats exp/tri4_nnet/final.mat ark:- ark:- | transform-feats --utt2spk=ark:data/train/split30/1/utt2spk ark:exp/tri3_ali/trans.1 ark:- ark:- | had nonzero return status 36096 feat-to-dim 'ark,s,cs:utils/subset_scp.pl --quiet 333 data/train/split30/1/feats.scp | apply-cmvn --utt2spk=ark:data/train/split30/1/utt2spk scp:data/train/split30/1/cmvn.scp scp:- ark:- | splice-feats --left-context=3 --right-context=3 ark:- ark:- | transform-feats exp/tri4_nnet/final.mat ark:- ark:- | transform-feats --utt2spk=ark:data/train/split30/1/utt2spk ark:exp/tri3_ali/trans.1 ark:- ark:- | splice-feats --left-context=4 --right-context=4 ark:- ark:- |' - transform-feats exp/tri4_nnet/final.mat ark:- ark:- apply-cmvn --utt2spk=ark:data/train/split30/1/utt2spk scp:data/train/split30/1/cmvn.scp scp:- ark:- transform-feats --utt2spk=ark:data/train/split30/1/utt2spk ark:exp/tri3_ali/trans.1 ark:- ark:- splice-feats --left-context=4 --right-context=4 ark:- ark:- splice-feats --left-context=3 --right-context=3 ark:- ark:- WARNING (feat-to-dim[5.2]:Close():kaldi-io.cc:501) Pipe utils/subset_scp.pl --quiet 333 data/train/split30/1/feats.scp | apply-cmvn --utt2spk=ark:data/train/split30/1/utt2spk scp:data/train/split30/1/cmvn.scp scp:- ark:- | splice-feats --left-context=3 --right-context=3 ark:- ark:- | transform-feats exp/tri4_nnet/final.mat ark:- ark:- | transform-feats --utt2spk=ark:data/train/split30/1/utt2spk ark:exp/tri3_ali/trans.1 ark:- ark:- | splice-feats --left-context=4 --right-context=4 ark:- ark:- | had nonzero return status 36096 steps/nnet2/get_lda.sh: Accumulating LDA statistics. steps/nnet2/get_lda.sh: Finished estimating LDA steps/nnet2/train_tanh.sh: calling get_egs.sh steps/nnet2/get_egs.sh --transform-dir exp/tri3_ali --splice-width 4 --samples-per-iter 200000 --num-jobs-nnet 30 --stage 0 --cmd run.pl --max-jobs-run 10 --io-opts --max-jobs-run 5 data/train data/lang exp/tri3_ali exp/tri4_nnet steps/nnet2/get_egs.sh: feature type is lda steps/nnet2/get_egs.sh: using transforms from exp/tri3_ali steps/nnet2/get_egs.sh: working out number of frames of training data utils/data/get_utt2dur.sh: segments file does not exist so getting durations from wave files utils/data/get_utt2dur.sh: successfully obtained utterance lengths from sphere-file headers utils/data/get_utt2dur.sh: computed data/train/utt2dur feat-to-len 'scp:head -n 10 data/train/feats.scp|' ark,t:- steps/nnet2/get_egs.sh: Every epoch, splitting the data up into 1 iterations, steps/nnet2/get_egs.sh: giving samples-per-iteration of 37740 (you requested 200000). Getting validation and training subset examples. steps/nnet2/get_egs.sh: extracting validation and training-subset alignments. copy-int-vector ark:- ark,t:- LOG (copy-int-vector[5.2]:main():copy-int-vector.cc:83) Copied 3696 vectors of int32. Getting subsets of validation examples for diagnostics and combination. Creating training examples Generating training examples on disk steps/nnet2/get_egs.sh: rearranging examples into parts for different parallel jobs steps/nnet2/get_egs.sh: Since iters-per-epoch == 1, just concatenating the data. Shuffling the order of training examples (in order to avoid stressing the disk, these won't all run at once). steps/nnet2/get_egs.sh: Finished preparing training examples steps/nnet2/train_tanh.sh: initializing neural net Training transition probabilities and setting priors steps/nnet2/train_tanh.sh: Will train for 15 + 5 epochs, equalling steps/nnet2/train_tanh.sh: 15 + 5 = 20 iterations, steps/nnet2/train_tanh.sh: (while reducing learning rate) + (with constant learning rate). Training neural net (pass 0) Training neural net (pass 1) Training neural net (pass 2) Training neural net (pass 3) Training neural net (pass 4) Training neural net (pass 5) Training neural net (pass 6) Training neural net (pass 7) Training neural net (pass 8) Training neural net (pass 9) Training neural net (pass 10) Training neural net (pass 11) Training neural net (pass 12) Mixing up from 1935 to 5000 components Training neural net (pass 13) Training neural net (pass 14) Training neural net (pass 15) Training neural net (pass 16) Training neural net (pass 17) Training neural net (pass 18) Training neural net (pass 19) Setting num_iters_final=5 Getting average posterior for purposes of adjusting the priors. Re-adjusting priors based on computed posteriors Done Cleaning up data steps/nnet2/remove_egs.sh: Finished deleting examples in exp/tri4_nnet/egs Removing most of the models steps/nnet2/decode.sh --cmd run.pl --max-jobs-run 10 --nj 5 --num-threads 6 --transform-dir exp/tri3/decode_dev exp/tri3/graph data/dev exp/tri4_nnet/decode_dev steps/nnet2/decode.sh: feature type is lda steps/nnet2/decode.sh: using transforms from exp/tri3/decode_dev steps/diagnostic/analyze_lats.sh --cmd run.pl --max-jobs-run 10 --iter final exp/tri3/graph exp/tri4_nnet/decode_dev steps/diagnostic/analyze_lats.sh: see stats in exp/tri4_nnet/decode_dev/log/analyze_alignments.log Overall, lattice depth (10,50,90-percentile)=(7,34,172) and mean=76.7 steps/diagnostic/analyze_lats.sh: see stats in exp/tri4_nnet/decode_dev/log/analyze_lattice_depth_stats.log score best paths score confidence and timing with sclite Decoding done. steps/nnet2/decode.sh --cmd run.pl --max-jobs-run 10 --nj 5 --num-threads 6 --transform-dir exp/tri3/decode_test exp/tri3/graph data/test exp/tri4_nnet/decode_test steps/nnet2/decode.sh: feature type is lda steps/nnet2/decode.sh: using transforms from exp/tri3/decode_test steps/diagnostic/analyze_lats.sh --cmd run.pl --max-jobs-run 10 --iter final exp/tri3/graph exp/tri4_nnet/decode_test steps/diagnostic/analyze_lats.sh: see stats in exp/tri4_nnet/decode_test/log/analyze_alignments.log Overall, lattice depth (10,50,90-percentile)=(7,37,192) and mean=88.6 steps/diagnostic/analyze_lats.sh: see stats in exp/tri4_nnet/decode_test/log/analyze_lattice_depth_stats.log score best paths score confidence and timing with sclite Decoding done. ============================================================================ System Combination (DNN+SGMM) ============================================================================ ============================================================================ DNN Hybrid Training & Decoding (Karel's recipe) ============================================================================ steps/nnet/make_fmllr_feats.sh --nj 10 --cmd run.pl --max-jobs-run 10 --transform-dir exp/tri3/decode_test data-fmllr-tri3/test data/test exp/tri3 data-fmllr-tri3/test/log data-fmllr-tri3/test/data steps/nnet/make_fmllr_feats.sh: feature type is lda_fmllr utils/copy_data_dir.sh: copied data from data/test to data-fmllr-tri3/test Checking data-fmllr-tri3/test/text ... --> reading data-fmllr-tri3/test/text --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces utils/validate_data_dir.sh: Successfully validated data-directory data-fmllr-tri3/test steps/nnet/make_fmllr_feats.sh: Done!, type lda_fmllr, data/test --> data-fmllr-tri3/test, using : raw-trans None, gmm exp/tri3, trans exp/tri3/decode_test steps/nnet/make_fmllr_feats.sh --nj 10 --cmd run.pl --max-jobs-run 10 --transform-dir exp/tri3/decode_dev data-fmllr-tri3/dev data/dev exp/tri3 data-fmllr-tri3/dev/log data-fmllr-tri3/dev/data steps/nnet/make_fmllr_feats.sh: feature type is lda_fmllr utils/copy_data_dir.sh: copied data from data/dev to data-fmllr-tri3/dev Checking data-fmllr-tri3/dev/text ... --> reading data-fmllr-tri3/dev/text --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces utils/validate_data_dir.sh: Successfully validated data-directory data-fmllr-tri3/dev steps/nnet/make_fmllr_feats.sh: Done!, type lda_fmllr, data/dev --> data-fmllr-tri3/dev, using : raw-trans None, gmm exp/tri3, trans exp/tri3/decode_dev steps/nnet/make_fmllr_feats.sh --nj 10 --cmd run.pl --max-jobs-run 10 --transform-dir exp/tri3_ali data-fmllr-tri3/train data/train exp/tri3 data-fmllr-tri3/train/log data-fmllr-tri3/train/data steps/nnet/make_fmllr_feats.sh: feature type is lda_fmllr utils/copy_data_dir.sh: copied data from data/train to data-fmllr-tri3/train Checking data-fmllr-tri3/train/text ... --> reading data-fmllr-tri3/train/text --> text seems to be UTF-8 or ASCII, checking whitespaces --> text contains only allowed whitespaces utils/validate_data_dir.sh: Successfully validated data-directory data-fmllr-tri3/train steps/nnet/make_fmllr_feats.sh: Done!, type lda_fmllr, data/train --> data-fmllr-tri3/train, using : raw-trans None, gmm exp/tri3, trans exp/tri3_ali utils/subset_data_dir_tr_cv.sh data-fmllr-tri3/train data-fmllr-tri3/train_tr90 data-fmllr-tri3/train_cv10 /home/houwenbin/kaldi-master/egs/timit/s5/utils/subset_data_dir.sh: reducing #utt from 3696 to 3320 /home/houwenbin/kaldi-master/egs/timit/s5/utils/subset_data_dir.sh: reducing #utt from 3696 to 376 LOG ([5.2]:main():cuda-gpu-available.cc:86) ... ### WE DID NOT GET A CUDA GPU!!! ### ### If your system has a 'free' CUDA GPU, try re-installing latest 'CUDA toolkit' from NVidia (this updates GPU drivers too). ### Otherwise 'nvidia-smi' shows the status of GPUs: ### - The versions should match ('NVIDIA-SMI' and 'Driver Version'), otherwise reboot or reload kernel module, ### - The GPU should be unused (no 'process' in list, low 'memory-usage' (<100MB), low 'gpu-fan' (<30%)), ### - You should see your GPU (burnt GPUs may disappear from the list until reboot), # Accounting: time=0 threads=1 # Ended (code 1) at Mon Nov 27 16:29:09 CST 2017, elapsed time 0 seconds # steps/nnet/pretrain_dbn.sh --hid-dim 1024 --rbm-iter 20 data-fmllr-tri3/train exp/dnn4_pretrain-dbn # Started at Mon Nov 27 23:16:11 CST 2017 # steps/nnet/pretrain_dbn.sh --hid-dim 1024 --rbm-iter 20 data-fmllr-tri3/train exp/dnn4_pretrain-dbn # INFO steps/nnet/pretrain_dbn.sh : Pre-training Deep Belief Network as a stack of RBMs dir : exp/dnn4_pretrain-dbn Train-set : data-fmllr-tri3/train '3696' LOG ([5.2]:main():cuda-gpu-available.cc:49) ### IS CUDA GPU AVAILABLE? 'localhost.localdomain' ### ERROR ([5.2]:SelectGpuId():cu-device.cc:121) No CUDA GPU detected!, diagnostics: cudaError_t 35 : "CUDA driver version is insufficient for CUDA runtime version", in cu-device.cc:121 [ Stack-Trace: ] kaldi::MessageLogger::HandleMessage(kaldi::LogMessageEnvelope const&, char const*) kaldi::MessageLogger::~MessageLogger() kaldi::CuDevice::SelectGpuId(std::string) main __libc_start_main cuda-gpu-available() [0x401739] LOG ([5.2]:main():cuda-gpu-available.cc:86) ... ### WE DID NOT GET A CUDA GPU!!! ### ### If your system has a 'free' CUDA GPU, try re-installing latest 'CUDA toolkit' from NVidia (this updates GPU drivers too). ### Otherwise 'nvidia-smi' shows the status of GPUs: ### - The versions should match ('NVIDIA-SMI' and 'Driver Version'), otherwise reboot or reload kernel module, ### - The GPU should be unused (no 'process' in list, low 'memory-usage' (<100MB), low 'gpu-fan' (<30%)), ### - You should see your GPU (burnt GPUs may disappear from the list until reboot), # Accounting: time=0 threads=1 # Ended (code 1) at Mon Nov 27 23:16:11 CST 2017, elapsed time 0 seconds run.pl: job failed, log is in exp/dnn4_pretrain-dbn/log/pretrain_dbn.log [houwenbin@localhost s5]$
程序会在这里中断,参照:http://blog.csdn.net/lindadasummer/article/details/77727193
exit 0 # From this point you can run Karel's DNN : local/nnet/run_dnn.sh
继续运行吧!!!
等了一晚上,悲催了,服务器上没有GPU,实验不能继续了,作罢,不过基本步骤都已经有了,剩下就去研究流程了~~~~
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