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第5行： |
| | * nplm: NN LM, large scale data [http://nlg.isi.edu/software/nplm/] | | * nplm: NN LM, large scale data [http://nlg.isi.edu/software/nplm/] |
| | * RNN toolkit from microsoft [http://research.microsoft.com/en-us/projects/rnn/] | | * RNN toolkit from microsoft [http://research.microsoft.com/en-us/projects/rnn/] |
| | + | * cslm [http://www-lium.univ-lemans.fr/~cslm/] |
| | | | |
| | ==paper== | | ==paper== |
| | + | *[[14-9-30]] |
| | + | *[[2014-10-9]] |
| | + | |
| | ==Steps== | | ==Steps== |
| | [[process dict and data]] | | [[process dict and data]] |
| − | ==wsj Test== | + | ==Test== |
| − | | + | *[[wsj_data]] |
| − | === wsj_data ===
| + | *[[chinese_data_gigword]] |
| − | *Data | + | *[[jt-chinese]] |
| − | :* size:200M,npdata
| + | |
| − | *parameter
| + | |
| − | rand_seed=1
| + | |
| − | nwords=10000 # This is how many words we're putting in the vocab of the RNNLM.
| + | |
| − | hidden=320
| + | |
| − | class=300 # Num-classes... should be somewhat larger than sqrt of nwords.
| + | |
| − | direct=2000 # Number of weights that are used for "direct" connections, in millions.
| + | |
| − | rnnlm_ver=rnnlm-0.3e # version of RNNLM to use
| + | |
| − | threads=1 # for RNNLM-HS
| + | |
| − | bptt=2 # length of BPTT unfolding in RNNLM
| + | |
| − | bptt_block=20 # length of BPTT unfolding in RNNLM
| + | |
| − | *Train RNNLM set
| + | |
| − | | + | |
| − | {| border="2px"
| + | |
| − | |+ Train Set Environment
| + | |
| − | |-
| + | |
| − | ! Parameters !! hidden !! class !! direct !! bbt !! bptt_block !! threads !!direct-order!!rand_seed!!nwords!!time(min)
| + | |
| − | |-
| + | |
| − | !set1
| + | |
| − | | 320 || 300 || 2000 || 2 || 20 || 1 || 4 || 1 || 10000||3380(56h)
| + | |
| − | |-
| + | |
| − | |}
| + | |
| − | | + | |
| − | ===RNNLM Rescore===
| + | |
| − | *Acoustic Model
| + | |
| − | ** location: /nfs/disk/work/users/zhangzy/work/train_wsj_eng_new/data/train_si284
| + | |
| − | **
| + | |
| − | *test set
| + | |
| − | ** location: /nfs/disk/work/users/zhangzy/work/train_wsj_eng_new/dt/test_eval92
| + | |
| − | ** decode: /nfs/disk/work/users/zhangzy/work/train_wsj_eng_new/exp/tri4b_dnn_org/decode_eval92_tri4b_dnn_org
| + | |
| − | *Result
| + | |
| − | ** lm:4.16%,rnnlm:3.47%
| + | |
| − | | + | |
| − | ==chinese data==
| + | |
| − | ===prepare data===
| + | |
| − | *now data
| + | |
| − | ** gigaword: /work2/xingchao/corpus/Chinese_corpus/gigaword
| + | |
| − | ** bing parallel corpus:/nfs/disk/work/users/xingchao/bing_dict
| + | |
| − | ** baidu:
| + | |
| − | ** sougou:
| + | |
| − | * using data
| + | |
| − | ** sample gigword about 344M
| + | |
| − | ** dict:tencent11w
| + | |
| − | *train set
| + | |
| − | | + | |
| − | {| border="2px"
| + | |
| − | |+ Train Set Environment
| + | |
| − | |-
| + | |
| − | ! Parameters !! hidden !! class !! direct !! bbt !! bptt_block !! threads !!direct-order!!rand_seed!!nwords!!time(min)
| + | |
| − | |-
| + | |
| − | !set1
| + | |
| − | | 320 || 300 || 2000 || 2 || 20 || 1 || 4 || 1 || 10000||3380(56h)
| + | |
| − | |-
| + | |
| − | |}
| + | |
