TODO

BUGS:
	-text2wdngram has a bug. 

TODOLIST 
-Generate random sentences from a language model.   (Add Atoth's code)
-addone in Waterloo LM toolkit
-null smoothing
-Incorporate Prof. Esteve's Kneyser Ney smoothing.
-Merge the ng_t and arpa_ng_t.  The only differ from each other by two
variables. (used ng_t) -> build something like arpa2binlm.  
-> Implement at least one word clustering algorithm (Brown's algorithm
like in SRI or HTK's algorithm) 
-> Implement some kind of ME type of training. 
-> Test the code when there are 1 billion words in
-> Test the code when there are 1 million words and train a 10 grams
-> Implement at least one method to prune the n-gram
-> Should we implement clustering like HTK. 

-> Implement PALM tk functionalities: reverseword
				    : reverseidngram
				    : mixidngram
				    : text2idtex

-> Make sure that by default, the output of files will generate not
generate results into stdout. 

Thoroughly test the following tool in 16bit mode and 32bit mode
interpolate
mergeidngram
ngram2mgram

text2wngram
lm_combine
wngram2idngram

Done 

SRI LM Toolkit replace word with word class.  This could be done by
class_tagger.pl which is in some sense even more flexible because
regular expression could be used.