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README: how to use the example mains for speech recognition
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Files:
phonemes_*: contain the list of acceptable phonemes for the problem
dict_*: contains the list of acceptable words for the problem: they should
of course be constituted of acceptable phonemes. special words <s> and </s>
are start and end words
train_files: contains the list of training files, in HTK format
train_word and train_aligned_word: contains the list of target files,
using HTK standards: either one word per line, or something like this:
0 2250000 h#
2250000 3625000 th+r
3625000 4375000 th-r+iy
4375000 6500000 r-iy
6500000 6750000 h#
6750000 8875000 s+ih
8875000 10000000 s-ih+kcl
10000000 10875000 ih-kcl+k
10875000 11375000 kcl-k+s
11375000 15500000 k-s
15500000 17500000 h#
which also contains the alignment. This helps the initialization step.
Programs:
speech_hmm_init.cc: to initialize models using KMeans. Example of usage:
Linux_OPT_FLOAT/speech_hmm_init -train_separate -threshold 0.2 -iter 100 -htk_model -save hmm_init_model -n_gaussians 10 phonemes_tri dict_tri train_files train_align_tri
speech_hmm_train.cc: to train the models. Example of usage:
Linux_OPT_FLOAT/speech_hmm_train -add_sil_to_targets -iter 40 -viterbi -htk_model -save hmm_model_viterbi -threshold 0.2 phonemes_tri dict_tri train_files train_word hmm_init_model
speech_hmm_simple_decode.cc: to decode using simple decoder (no large vocab):
Linux_OPT_FLOAT/speech_hmm_simple_decode -htk_model -log_word_entrance_penalty -15 -add_sil_to_targets hmm_model_viterbi phonemes_tri dict_tri train_files train_word
speech_hmm_tode_decode.cc: to decode using TODE decoder (for large vocab):
Linux_OPT_FLOAT/speech_hmm_tode_decode -htk_model -log_word_entrance_penalty -15 hmm_model_viterbi phonemes_tri dict_tri train_files train_word
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