/**
* @file acconfig.h
*
*
* @brief config.h.in を configure.in から生成するための autoconf 用ヘッダ
*
* このファイルはソースからインクルードされることはありません.
* 実際にはこの内容は config.h.in に埋め込まれており，
* configure によって config.h.in から生成された config.h が
* プログラムによって使用されます.
*
* @sa config.h, config.h.in, configure, configure.in
*
*
*
* @brief Autoconf header to generate config.h.in from configure.in
*
* This file is not included by any source file. The contents of this file
* is already included in config.h.in, and the configuration script "configure"
* will generate config.h from config.h.in. It sets definitions according to
* the running environment and user-specified setting. The final config.h
* will be included by the sources.
*
* @sa config.h, config.h.in, configure, configure.in
*
*
* @author Akinobu LEE
* @date Sat Feb 19 12:53:54 2005
*
* $Revision: 1.2 $
*
*/
/// Name of the Product.
#undef PRODUCTNAME
/// Version string
#undef VERSION
/// Engine setting (value of "--enable-setup=...").
#undef SETUP
/// Compilation host information
#undef HOSTINFO
@TOP@
/// For Julius, defined if using 1-gram factoringon the 1st pass instead of 2-gram factoring.
#undef UNIGRAM_FACTORING
/**
* For Julius, defined if dictionary forms a single tree lexicon, sharing
* only a single root node. This saves memory of inter-word LM cache.
*
*/
#undef LOWMEM
/**
* For Julius, defined if frequent words should be separated from the lexicon
* tree. This will improve accuracy on small beam, and default of "fast"
* setting. If none of LOWMEM and LOWMEM2 is defined, separation of short
* words from lexicon tree will be performed to get the better accuracy, at
* a cost of LM cache area on word head.
*
*/
#undef LOWMEM2
/**
* If defined, use word-pair approximation on the 1st pass instead of
* 1-best approximation.
*
*/
#undef WPAIR
/**
* When WPAIR is defined, only up to N tokens will be kept for each node
* instead of keeping tokens depending on the previous word. This may
* improve memory efficiency when word-pair approximation is used.
*
*/
#undef WPAIR_KEEP_NLIMIT
/**
* If defined, generate a simple word graph instead of word trellis on
* the 1st pass. This limits word expansion on the 2nd pass
* to only the words on the word graph, and the final recognition accuracy
* can be decreased. You should enable this with WPAIR to get reasonable
* output. Please note that this is different
* from Word Graph Output of the 2nd pass which can be enabled by GRAPHOUT.
*
*/
#undef WORD_GRAPH
/**
* If defined, use monophone tree lexicon on the 1st pass for speed up
* the search. This is EXPERIMENTAL, and should not be used.
*
*/
#undef MONOTREE
/**
* Handle inter-word triphone on the 1st pass. This should be defined
* if using context-dependent acoustic model. If not defined, the context
* will not be considered any more. This is defined by default.
*
*/
#undef PASS1_IWCD
/**
* On word expansion of the 2nd pass, Julius and Julian by default does
* not handle inter-word context dependency of the newly expanded words
* on the expansion time, and they will be computed when the hypothesis
* is popped from the stack at the later processing. If PASS2_STRICT_IWCD
* is defined, a strict inter-word triphone will be computed just on the
* word expansion time, by re-computing word edge phones on the connection
* point for all the word candidates.
*
* This option will results in a better
* recognition accuracy. However, the 2nd pass will become slower by the
* increasing acoustic matching cost.
*
*/
#undef PASS2_STRICT_IWCD
/**
* Enable score envelope beaming on the hypothesis scoring in the 2nd pass.
* This will be defined by default.
*
*/
#undef SCAN_BEAM
/// Set the default method of Gaussian pruning for tied-mixture model to safe algorithm
#undef GPRUNE_DEFAULT_SAFE
/// Set the default method of Gaussian pruning for tied-mixture model to heuristic algorithm
#undef GPRUNE_DEFAULT_HEURISTIC
/// Set the default method of Gaussian pruning for tied-mixture model to beam algorithm
#undef GPRUNE_DEFAULT_BEAM
/**
* Enables confidence scoring for the output words. This will be defined
* by default.
*
*/
#undef CONFIDENCE_MEASURE
/* use N-best confidence measure instead of search-time computation */
/**
* By default, Julius/Julian uses search-time heuristic scores to get the
* posterior probability based word confidence measures on the search time.
* This default algorithm can output word confidence scores with a little
* additional computation without searching for much sentences.
*
* If you still use a trivial method of computing the word confidence scores
* from the N-best sentence list, you can define this.
*
*/
#undef CM_NBEST
/**
* If defined, compute confidence scores for multiple alpha values.
*
*/
#undef CM_MULTIPLE_ALPHA
/**
* Enable search space visualization feature. You need X11 and GTK to
* use this.
*
*/
#undef VISUALIZE
/**
* When VISUALIZE is defind, this defines a command to play the recorded
* sound on the visualization window.
*/
#undef PLAYCOMMAND
/**
* On Julius, if defined, fix some language model scoring bug on the 2nd pass.
*
*/
#undef LM_FIX_DOUBLE_SCORING
/**
* Use dynamic word graph generation on the 2nd pass.
* The word candidates are fixed as soon as the word boundary is fixed
* in search, and as soon as same word appears in the same position,
* they will be merged. It results in much more words to be
* remained in the graph.
*
*/
#undef GRAPHOUT_DYNAMIC
/**
* If defined with GRAPHOUT_DYNAMIC, use modified stack
* decoding algorithm for efficient word graph generation.
*
*/
#undef GRAPHOUT_SEARCH
/**
* If defined, avoid expansion of low CM word on search. This may
* speed up
*
*/
#undef CM_SEARCH_LIMIT
/**
* If defined, enable decoder-oriented VAD using short-pause segmentation
* scheme developed by NAIST team
*
*/
#undef SPSEGMENT_NAIST
/**
* If defined, enable a simple GMM-based VAD. Both frontend VAD and
* postprocessing rejection will be performed using the same GMM.
*
*/
#undef GMM_VAD
/**
* This will be defined internally when in-decoder type VAD is enabled.
*
*/
#undef BACKEND_VAD
/**
* If enabled, do post-rejection by power
*
*/
#undef POWER_REJECT