---
name: "slmbuild"
section: "1"
platform: "linux"
package: "sunpinyin"
version: "3.0.0rc2-3"
release: "Arch Linux 2026-11-01"
platforms: ["linux"]
url: "https://new.carta.tech/slmbuild"
---

# slmbuild(1)

generate language model from idngram file

## NAME

slmbuild - generate language model from idngram file

## SYNOPSIS

slmbuild \[*option*\]... *idngram\_file*...

## DESCRIPTION

**slmbuild** generates a back-off smoothing language model from a given idngram file. Generally, the *idngram\_file* is created by **ids2ngram**.

## OPTIONS All the following options are mandatory.

- **-n**,**--NMax** *N*

  1 for unigram, 2 for bigram, 3 for trigram. Any number not in the range of 1..3 is not valid.

- **-o**, **--out** *output-file*

  Specify the output xfilei name.

- **-l**, **--log**

  using *-log(pr)*, use *pr* directly by default.

- **-w**, **--wordcount** *N*

  Lexican size, number of different words.

- **-b**, **--brk** *id*...

  Set the ids which should be treated as breaker.

- **-e**, **--e** *id*...

  Set the ids which should not be put into LM.

- **-c**, **--cut** *c*...

  k-grams whose freq \<= c\[k\] are dropped.

- **-d**, **--discount** *method*, *param*...

  The k-th **-d** parm specifies the discount method

  For k-gram, possibble values for method/param are:

  ```
        B<GT>,I<R>,I<dis>  : B<GT> discount for r E<lt>= I<R>, r is the freq of a ngram.
                    Linear discount for those r E<gt> I<R>, i.e. r'=r*dis
                    0 E<lt>E<lt> dis E<lt> 1.0, for example 0.999
        B<ABS>,[I<dis>] : Absolute discount r'=r-I<dis>. And I<dis> is optional
                    0 E<lt>E<lt> I<dis> E<lt> cut[k]+1.0, normally I<dis> E<lt> 1.0.
        LIN,[I<dis>] : Linear discount r'=r*dis. And dis is optional
                    0 E<lt> dis E<lt> 1.0
  ```

## NOTE

**-n** must be given before **-c** **-b**. And **-c** must give right number of cut-off, also **-d**s must appear exactly N times specifying the discounts for 1-gram, 2-gram...,  respectively.

BREAKER-IDs could be SentenceTokens or ParagraphTokens. Conceptually, these ids have no meaning when they appeared in the middle of n-gram.

EXCLUDE-IDs could be ambiguious-ids. Conceptually, n-grams which contain those ids are meaningless.

We can not erase ngrams according to BREAKER-IDS and EXCLUDE-IDs directly from IDNGRAM file, because some low-level information is still useful in it.

## EXAMPLE

Following example read 'all.id3gram' and write trigram model 'all.slm'.

At 1-gram level, use Good-Turing discount with cut-off 0, i\<R\>=8, *dis*=0.9995. At 2-gram level, use Absolute discount with cut-off 3, dis auto-calc. At 3-gram level, use Absolute discount with cut-off 2, dis auto-calc. Word id 10,11,12 are breakers (sentence/para/paper breaker, etc). Exclude-ID is 9. Lexicon  contains 200000 words. The result languagme model uses -log(pr).

**slmbuild -l -n 3 -o all.slm -w 200000 -c 0,3,2 -d GT,8,0.9995 -d ABS -d ABS -b 10,11,12 -e 9 all.id3gram**

## AUTHOR

Originally written by Phill.Zhang \<phill.zhang@sun.com\>. Currently maintained by Kov.Chai \<tchaikov@gmail.com\>.

## SEE ALSO

[**ids2ngram**(1)](/ids2ngram/1.md), [**slmprune**(1)](/slmprune/1.md).