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			3.5 KiB
		
	
	
	
		
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			38 lines
		
	
	
		
			3.5 KiB
		
	
	
	
		
			Plaintext
		
	
	
	
	
	
|   | File(3)                  - Wrapper for stdio streams | ||
|  | LM(3)                    - Generic language model | ||
|  | Prob(3)                  - Probabilities for SRILM | ||
|  | TEMPLATE(1), XXX(1)      - XXX | ||
|  | TEMPLATE(3), XXX(3)      - XXX | ||
|  | TEMPLATE(5), XXX(5)      - XXX | ||
|  | TEMPLATE(7), XXX(7)      - XXX | ||
|  | Vocab(3)                 - Vocabulary indexing for SRILM | ||
|  | anti-ngram(1)            - count posterior-weighted N-grams in N-best lists | ||
|  | classes-format(5)        - File format for word class definitions | ||
|  | disambig(1)              - disambiguate text tokens using an N-gram model | ||
|  | hidden-ngram(1)          - tag hidden events between words | ||
|  | lattice-tool(1)          - manipulate word lattices | ||
|  | lm-scripts(1), add-dummy-bows(1), change-lm-vocab(1), empty-sentence-lm(1), get-unigram-probs(1), make-hiddens-lm(1), make-lm-subset(1), make-sub-lm(1), remove-lowprob-ngrams(1), reverse-lm(1), sort-lm(1) - manipulate N-gram language models | ||
|  | metadb(1)                - retrieve configuration information | ||
|  | multi-ngram(1)           - build multiword N-gram models | ||
|  | nbest-format(5)          - File formats for N-best hypotheses lists | ||
|  | nbest-lattice(1)         - rescore N-best lists and lattices | ||
|  | nbest-mix(1)             - interpolate N-best posterior probabilities | ||
|  | nbest-optimize(1)        - optimize score combination for N-best word error minimization | ||
|  | nbest-pron-score(1)      - score pronunciations and pauses in N-best hypotheses | ||
|  | nbest-scripts(1), combine-rover-controls(1), compare-sclite(1), compute-sclite(1), fix-ctm(1), merge-nbest(1), nbest-error(1), nbest-posteriors(1), nbest-rover(1), nbest-vocab(1), nbest2-to-nbest1(1), rescore-acoustic(1), rescore-decipher(1), rescore-reweight(1), sentid-to-sclite(1) - rescore and evaluate N-best lists | ||
|  | ngram(1)                 - apply N-gram language models | ||
|  | ngram-class(1)           - induce word classes from N-gram statistics | ||
|  | ngram-count(1)           - count N-grams and estimate language models | ||
|  | ngram-discount(7)        - notes on the N-gram smoothing implementations in SRILM | ||
|  | ngram-format(5)          - File format for ARPA backoff N-gram models | ||
|  | ngram-merge(1)           - merge N-gram counts | ||
|  | pfsg-format(5)           - File format for Decipher(TM) probabilistic finite-state grammars | ||
|  | pfsg-scripts(1), add-classes-to-pfsg(1), add-pauses-to-pfsg(1), classes-to-fsm(1), fsm-to-pfsg(1), htklat-vocab(1), make-nbest-pfsg(1), make-ngram-pfsg(1), pfsg-from-ngram(1), pfsg-to-dot(1), pfsg-to-fsm(1), pfsg-vocab(1), wlat-stats(1), wlat-to-dot(1), wlat-to-pfsg(1) - create and manipulate finite-state networks | ||
|  | ppl-scripts(1), add-ppls(1), compare-ppls(1), compute-best-mix(1), compute-best-sentence-mix(1), jilter-event-counts(1), hits-from-log(1), ppl-from-log(1), subtract-ppls(1) - manipulate perplexities | ||
|  | segment(1)               - segment text using N-gram language model | ||
|  | segment-nbest(1)         - rescore and segment N-best lists using hidden segment N-gram model | ||
|  | select-vocab(1)          - Select a maximum-likelihood vocabulary from a mixture of corpora | ||
|  | srilm-faq(7), SRILM-FAQ(7) - Frequently asked questions about SRI LM tools | ||
|  | training-scripts(1), compute-oov-rate(1), continuous-ngram-count(1), get-gt-counts(1), make-abs-discount(1), make-batch-counts(1), make-big-lm(1), make-diacritic-map(1),  make-google-ngrams(1), make-gt-discounts(1), make-kn-counts(1), make-kn-discounts(1), merge-batch-counts(1), replace-words-with-classes(1), reverse-ngram-counts(1), split-tagged-ngrams(1), reverse-text(1), tolower-ngram-counts(1), uniform-classes(1), uniq-ngram-counts(1), vp2text(1) - miscellaneous conveniences for language model training | ||
|  | wlat-format(5)           - File format for SRILM word posterior lattices |