我想在linux平台上将语音文件转换为文本文件。在研究方面，我得到了pocketsphinx语音识别工具。在post的帮助下。我使用了以下命令
pocketsphinx_continuous -infile file.wav
file.wav是16bit，16Khz和单声道。
输出
INFO: pocketsphinx.c(152): Parsed model-specific feature parameters from /usr/local/share/pocketsphinx/model/en-us/en-us/feat.params
Current configuration:
[NAME] [DEFLT] [VALUE]
-agc none none
-agcthresh 2.0 2.000000e+00
-allphone
-allphone_ci no no
-alpha 0.97 9.700000e-01
-ascale 20.0 2.000000e+01
-aw 1 1
-backtrace no no
-beam 1e-48 1.000000e-48
-bestpath yes yes
-bestpathlw 9.5 9.500000e+00
-ceplen 13 13
-cmn current current
-cmninit 8.0 40,3,-1
-compallsen no no
-debug 0
-dict /usr/local/share/pocketsphinx/model/en-us/cmudict-en-us.dict
-dictcase no no
-dither no no
-doublebw no no
-ds 1 1
-fdict
-feat 1s_c_d_dd 1s_c_d_dd
-featparams
-fillprob 1e-8 1.000000e-08
-frate 100 100
-fsg
-fsgusealtpron yes yes
-fsgusefiller yes yes
-fwdflat yes yes
-fwdflatbeam 1e-64 1.000000e-64
-fwdflatefwid 4 4
-fwdflatlw 8.5 8.500000e+00
-fwdflatsfwin 25 25
-fwdflatwbeam 7e-29 7.000000e-29
-fwdtree yes yes
-hmm /usr/local/share/pocketsphinx/model/en-us/en-us
-input_endian little little
-jsgf
-keyphrase
-kws
-kws_delay 10 10
-kws_plp 1e-1 1.000000e-01
-kws_threshold 1 1.000000e+00
-latsize 5000 5000
-lda
-ldadim 0 0
-lifter 0 22
-lm /usr/local/share/pocketsphinx/model/en-us/en-us.lm.bin
-lmctl
-lmname
-logbase 1.0001 1.000100e+00
-logfn
-logspec no no
-lowerf 133.33334 1.300000e+02
-lpbeam 1e-40 1.000000e-40
-lponlybeam 7e-29 7.000000e-29
-lw 6.5 6.500000e+00
-maxhmmpf 30000 30000
-maxwpf -1 -1
-mdef
-mean
-mfclogdir
-min_endfr 0 0
-mixw
-mixwfloor 0.0000001 1.000000e-07
-mllr
-mmap yes yes
-ncep 13 13
-nfft 512 512
-nfilt 40 25
-nwpen 1.0 1.000000e+00
-pbeam 1e-48 1.000000e-48
-pip 1.0 1.000000e+00
-pl_beam 1e-10 1.000000e-10
-pl_pbeam 1e-10 1.000000e-10
-pl_pip 1.0 1.000000e+00
-pl_weight 3.0 3.000000e+00
-pl_window 5 5
-rawlogdir
-remove_dc no no
-remove_noise yes yes
-remove_silence yes yes
-round_filters yes yes
-samprate 16000 1.600000e+04
-seed -1 -1
-sendump
-senlogdir
-senmgau
-silprob 0.005 5.000000e-03
-smoothspec no no
-svspec 0-12/13-25/26-38
-tmat
-tmatfloor 0.0001 1.000000e-04
-topn 4 4
-topn_beam 0 0
-toprule
-transform legacy dct
-unit_area yes yes
-upperf 6855.4976 6.800000e+03
-uw 1.0 1.000000e+00
-vad_postspeech 50 50
-vad_prespeech 20 20
-vad_startspeech 10 10
-vad_threshold 2.0 2.000000e+00
-var
-varfloor 0.0001 1.000000e-04
-varnorm no no
-verbose no no
-warp_params
-warp_type inverse_linear inverse_linear
-wbeam 7e-29 7.000000e-29
-wip 0.65 6.500000e-01
-wlen 0.025625 2.562500e-02
INFO: feat.c(715): Initializing feature stream to type: '1s_c_d_dd', ceplen=13, CMN='current', VARNORM='no', AGC='none'
INFO: cmn.c(143): mean[0]= 12.00, mean[1..12]= 0.0
INFO: acmod.c(164): Using subvector specification 0-12/13-25/26-38
INFO: mdef.c(518): Reading model definition: /usr/local/share/pocketsphinx/model/en-us/en-us/mdef
INFO: mdef.c(531): Found byte-order mark BMDF, assuming this is a binary mdef file
INFO: bin_mdef.c(336): Reading binary model definition: /usr/local/share/pocketsphinx/model/en-us/en-us/mdef
INFO: bin_mdef.c(516): 42 CI-phone, 137053 CD-phone, 3 emitstate/phone, 126 CI-sen, 5126 Sen, 29324 Sen-Seq
INFO: tmat.c(206): Reading HMM transition probability matrices: /usr/local/share/pocketsphinx/model/en-us/en-us/transition_matrices
INFO: acmod.c(117): Attempting to use PTM computation module
INFO: ms_gauden.c(198): Reading mixture gaussian parameter: /usr/local/share/pocketsphinx/model/en-us/en-us/means
INFO: ms_gauden.c(292): 42 codebook, 3 feature, size:
INFO: ms_gauden.c(294): 128x13
INFO: ms_gauden.c(294): 128x13
INFO: ms_gauden.c(294): 128x13
INFO: ms_gauden.c(198): Reading mixture gaussian parameter: /usr/local/share/pocketsphinx/model/en-us/en-us/variances
INFO: ms_gauden.c(292): 42 codebook, 3 feature, size:
INFO: ms_gauden.c(294): 128x13
INFO: ms_gauden.c(294): 128x13
INFO: ms_gauden.c(294): 128x13
INFO: ms_gauden.c(354): 222 variance values floored
INFO: ptm_mgau.c(476): Loading senones from dump file /usr/local/share/pocketsphinx/model/en-us/en-us/sendump
INFO: ptm_mgau.c(500): BEGIN FILE FORMAT DESCRIPTION
INFO: ptm_mgau.c(563): Rows: 128, Columns: 5126
INFO: ptm_mgau.c(595): Using memory-mapped I/O for senones
INFO: ptm_mgau.c(835): Maximum top-N: 4
INFO: phone_loop_search.c(114): State beam -225 Phone exit beam -225 Insertion penalty 0
INFO: dict.c(320): Allocating 138623 * 20 bytes (2707 KiB) for word entries
INFO: dict.c(333): Reading main dictionary: /usr/local/share/pocketsphinx/model/en-us/cmudict-en-us.dict
INFO: dict.c(213): Allocated 1014 KiB for strings, 1677 KiB for phones
INFO: dict.c(336): 134522 words read
INFO: dict.c(358): Reading filler dictionary: /usr/local/share/pocketsphinx/model/en-us/en-us/noisedict
INFO: dict.c(213): Allocated 0 KiB for strings, 0 KiB for phones
INFO: dict.c(361): 5 words read
INFO: dict2pid.c(396): Building PID tables for dictionary
INFO: dict2pid.c(406): Allocating 42^3 * 2 bytes (144 KiB) for word-initial triphones
INFO: dict2pid.c(132): Allocated 21336 bytes (20 KiB) for word-final triphones
INFO: dict2pid.c(196): Allocated 21336 bytes (20 KiB) for single-phone word triphones
INFO: ngram_model_trie.c(347): Trying to read LM in trie binary format
INFO: ngram_search_fwdtree.c(99): 790 unique initial diphones
INFO: ngram_search_fwdtree.c(148): 0 root, 0 non-root channels, 57 single-phone words
INFO: ngram_search_fwdtree.c(186): Creating search tree
INFO: ngram_search_fwdtree.c(192): before: 0 root, 0 non-root channels, 57 single-phone words
INFO: ngram_search_fwdtree.c(326): after: max nonroot chan increased to 152144
INFO: ngram_search_fwdtree.c(339): after: 722 root, 152016 non-root channels, 53 single-phone words
INFO: ngram_search_fwdflat.c(157): fwdflat: min_ef_width = 4, max_sf_win = 25
INFO: continuous.c(307): pocketsphinx_continuous COMPILED ON: Mar 30 2016, AT: 12:15:51
INFO: ngram_search.c(467): Resized score stack to 200000 entries
INFO: ngram_search.c(459): Resized backpointer table to 10000 entries
INFO: cmn_prior.c(99): cmn_prior_update: from < 0.00 0.00 -nan 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 >
INFO: cmn_prior.c(116): cmn_prior_update: to < 47.48 0.98 -3.82 4.09 3.14 2.74 2.80 -12.69 -12.23 -5.07 6.26 -9.97 -3.79 >
INFO: ngram_search.c(467): Resized score stack to 400000 entries
INFO: ngram_search.c(459): Resized backpointer table to 20000 entries
INFO: cmn_prior.c(131): cmn_prior_update: from < 47.48 0.98 -3.82 4.09 3.14 2.74 2.80 -12.69 -12.23 -5.07 6.26 -9.97 -3.79 >
INFO: cmn_prior.c(149): cmn_prior_update: to < 46.64 -1.32 -1.28 2.40 -0.03 2.35 3.75 -12.45 -10.69 -4.19 5.41 -9.31 -3.67 >
INFO: ngram_search_fwdtree.c(1553): 10113 words recognized (10/fr)
INFO: ngram_search_fwdtree.c(1555): 826921 senones evaluated (857/fr)
INFO: ngram_search_fwdtree.c(1559): 2018242 channels searched (2091/fr), 83185 1st, 454283 last
INFO: ngram_search_fwdtree.c(1562): 19973 words for which last channels evaluated (20/fr)
INFO: ngram_search_fwdtree.c(1564): 157044 candidate words for entering last phone (162/fr)
INFO: ngram_search_fwdtree.c(1567): fwdtree 1.83 CPU 0.190 xRT
INFO: ngram_search_fwdtree.c(1570): fwdtree 1.84 wall 0.190 xRT
INFO: ngram_search_fwdflat.c(302): Utterance vocabulary contains 146 words
INFO: ngram_search_fwdflat.c(948): 6130 words recognized (6/fr)
INFO: ngram_search_fwdflat.c(950): 550472 senones evaluated (570/fr)
INFO: ngram_search_fwdflat.c(952): 702021 channels searched (727/fr)
INFO: ngram_search_fwdflat.c(954): 34182 words searched (35/fr)
INFO: ngram_search_fwdflat.c(957): 5373 word transitions (5/fr)
INFO: ngram_search_fwdflat.c(960): fwdflat 0.69 CPU 0.072 xRT
INFO: ngram_search_fwdflat.c(963): fwdflat 0.69 wall 0.072 xRT
INFO: ngram_search.c(1200): </s> not found in last frame, using watch.963 instead
INFO: ngram_search.c(1253): lattice start node <s>.0 end node watch.3
INFO: ngram_search.c(1279): Eliminated 498 nodes before end node
INFO: ngram_search.c(1384): Lattice has 634 nodes, 1 links
INFO: ps_lattice.c(1380): Bestpath score: -917
INFO: ps_lattice.c(1384): Normalizer P(O) = alpha(watch:3:963) = -1854347
INFO: ps_lattice.c(1441): Joint P(O,S) = -1854347 P(S|O) = 0
INFO: ngram_search.c(875): bestpath 0.00 CPU 0.000 xRT
INFO: ngram_search.c(878): bestpath 0.00 wall 0.000 xRT
watch
INFO: cmn_prior.c(131): cmn_prior_update: from < 46.64 -1.32 -1.28 2.40 -0.03 2.35 3.75 -12.45 -10.69 -4.19 5.41 -9.31 -3.67 >
INFO: cmn_prior.c(149): cmn_prior_update: to < 46.64 -1.32 -1.28 2.40 -0.03 2.35 3.75 -12.45 -10.69 -4.19 5.41 -9.31 -3.67 >
INFO: ngram_search_fwdflat.c(302): Utterance vocabulary contains 0 words
INFO: ngram_search_fwdtree.c(432): TOTAL fwdtree 1.83 CPU 0.190 xRT
INFO: ngram_search_fwdtree.c(435): TOTAL fwdtree 1.84 wall 0.190 xRT
INFO: ngram_search_fwdflat.c(176): TOTAL fwdflat 0.69 CPU 0.072 xRT
INFO: ngram_search_fwdflat.c(179): TOTAL fwdflat 0.69 wall 0.072 xRT
INFO: ngram_search.c(303): TOTAL bestpath 0.00 CPU 0.000 xRT
INFO: ngram_search.c(306): TOTAL bestpath 0.00 wall 0.000 xRT
使用此输出，我认为该工具会读取file.wav。但是，由于dict文件中的单词不可用，文本无法识别。我不知道我是否正确思考。
我甚至用过
pocketsphinx_continuous -infile brain_mono_8000.wav -hmm en_US/hub4wsj_sc_8k -lm en_US/hub4.5000.DMP
我收到了错误：
ERROR: "pocketsphinx.c", line 223: Failed to find mdef file inside the model folder specified with -hmm `en_US/hub4wsj_sc_8k'
有了这个错误，我就被困在这里了。为什么会出现这个错误？ 如何根据我的要求修改.dict文件。 请建议我。