kaldilm 1.13

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arpa2fst

Python wrapper for kaldi's arpa2fst.

Installation

kaldilm can be installed using either conda or pip.

Using conda

conda install -c k2-fsa -c conda-forge kaldilm

Using pip

pip install kaldilm

In case it doesn't work using pip install (you can't import _kaldilm), something likely failed during the compilation of the native part of this library. The following steps will show you a more verbose log that can help diagnose the issue:

# Remove the broken version first
pip uninstall kaldilm
pip install -v --no-cache-dir kaldilm

To test that kaldilm is installed successfully, run:

$ python3 -m kaldilm --help

It should display the usage information of kaldilm.

Please create an issue on GitHub if you encounter any problems while installing kaldilm.

Usage

First, let us see the usage information of kaldi's arpa2fst:

kaldi/src/lmbin$ ./arpa2fst
./arpa2fst

Convert an ARPA format language model into an FST
Usage: arpa2fst [opts] <input-arpa> <output-fst>
 e.g.: arpa2fst --disambig-symbol=#0 --read-symbol-table=data/lang/words.txt lm/input.arpa G.fst

Note: When called without switches, the output G.fst will contain
an embedded symbol table. This is compatible with the way a previous
version of arpa2fst worked.

Options:
  --bos-symbol                : Beginning of sentence symbol (string, default = "<s>")
  --disambig-symbol           : Disambiguator. If provided (e. g. #0), used on input side of backoff links, and <s> and </s> are replaced with epsilons (string, default = "")
  --eos-symbol                : End of sentence symbol (string, default = "</s>")
  --ilabel-sort               : Ilabel-sort the output FST (bool, default = true)
  --keep-symbols              : Store symbol table with FST. Symbols always saved to FST if symbol tables are neither read or written
(otherwise symbols would be lost entirely) (bool, default = false)
  --max-arpa-warnings         : Maximum warnings to report on ARPA parsing, 0 to disable, -1 to show all (int, default = 30)
  --read-symbol-table         : Use existing symbol table (string, default = "")
  --write-symbol-table        : Write generated symbol table to a file (string, default = "")

kaldilm uses the same arguments as kaldi's arpa2fst:

$ python3 -m kaldilm --help

prints

usage: Python wrapper of kaldi's arpa2fst [-h] [--bos-symbol BOS_SYMBOL]
                                          [--disambig-symbol DISAMBIG_SYMBOL]
                                          [--eos-symbol EOS_SYMBOL]
                                          [--ilabel-sort ILABEL_SORT]
                                          [--keep-symbols KEEP_SYMBOLS]
                                          [--max-arpa-warnings MAX_ARPA_WARNINGS]
                                          [--read-symbol-table READ_SYMBOL_TABLE]
                                          [--write-symbol-table WRITE_SYMBOL_TABLE]
                                          [--max-order MAX_ORDER]
                                          input_arpa [output_fst]

positional arguments:
  input_arpa            input arpa filename
  output_fst            Output fst filename. If empty, no output file is
                        created.

optional arguments:
  -h, --help            show this help message and exit
  --bos-symbol BOS_SYMBOL
                        Beginning of sentence symbol (default = "<s>")
  --disambig-symbol DISAMBIG_SYMBOL
                        Disambiguator. If provided (e.g., #0), used on input
                        side of backoff links, and <s> and </s> are replaced
                        with epsilons (default = "")
  --eos-symbol EOS_SYMBOL
                        End of sentence symbol (default = "</s>")
  --ilabel-sort ILABEL_SORT
                        Ilabel-sort the output FST (default = true)
  --keep-symbols KEEP_SYMBOLS
                        Store symbol table with FST. Symbols always saved to
                        FST if symboltables are neither read or written
                        (otherwise symbols would be lost entirely) (default =
                        false)
  --max-arpa-warnings MAX_ARPA_WARNINGS
                        Maximum warnings to report on ARPA parsing, 0 to
                        disable, -1 to show all (default = 30)
  --read-symbol-table READ_SYMBOL_TABLE
                        Use existing symbol table (default = "")
  --write-symbol-table WRITE_SYMBOL_TABLE
                        (Write generated symbol table to a file (default = "")
  --max-order MAX_ORDER
                        Maximum order (inclusive) in the arpa file is used to
                        generate the final FST. If it is -1, all ngram data in
                        the file are used.If it is 1, only unigram data are
                        used.If it is 2, only ngram data up to bigram are
                        used.Default is -1.

It has one extra argument --max-order, which is not present in kaldi's arpa2fst.

Example usage

Suppose you have an arpa file input.arpa with the following content:

\data\
ngram 1=4
ngram 2=2
ngram 3=2

\1-grams:
-5.234679	a -3.3
-3.456783	b
0.0000000	<s> -2.5
-4.333333	</s>

\2-grams:
-1.45678	a b -3.23
-1.30490	<s> a -4.2

\3-grams:
-0.34958	<s> a b
-0.23940	a b </s>

\end\

and the word symbol table is words.txt:

<eps> 0
a 1
b 2
#0 3
<s> 4
</s> 5

Caution: All symbols with ID >= the ID of #0 are set to <eps> during compiling HLG. See https://github.com/k2-fsa/icefall/blob/243fb9723cb82287ec5a891155ab9e0bc304740d/egs/librispeech/ASR/local/compile_hlg.py#L103 If IDs of <s> and </s> are less than that of #0, the resulting HLG is problematic.

You can use the following code to convert it into an FST.

3-gram

This uses all n-gram data inside the arpa file.

  python3 -m kaldilm \
    --read-symbol-table="./words.txt" \
    --disambig-symbol='#0' \
    ./input.arpa > G_fst.txt

The resulting G_fst.txt is shown in the following

3	5	1	1	3.00464
3	0	3	0	5.75646
0	1	1	1	12.0533
0	2	2	2	7.95954
0	9.97787
1	4	2	2	3.35436
1	0	3	0	7.59853
2	0	3	0
4	2	3	0	7.43735
4	0.551239
5	4	2	2	0.804938
5	1	3	0	9.67086

which can be visualized in k2 using

import k2
G = k2.Fsa.from_openfst(G_fst_txt, acceptor=False)
G.labels_sym = k2.SymbolTable.from_file('words.txt')
G.aux_labels_sym = k2.SymbolTable.from_file('words.txt')
#G.labels[G.labels >= 3] = 0 # convert symbols with ID >= ID of #0 to eps
G.draw('G.svg', title='G')

G.svg is shown below:

1-gram

It uses only uni-gram data inside the arpa file since --max-order=1 is used.

  python3 -m kaldilm \
    --read-symbol-table="./words.txt" \
    --disambig-symbol='#0' \
    --max-order=1 \
    ./input.arpa > G_uni_fst.txt

The generated G_uni_fst.txt is

3	0	3	0	5.75646
0	1	1	1	12.0533
0	2	2	2	7.95954
0	9.97787
1	0	3	0	7.59853
2	0	3	0

which can be visualized in k2 using

with open('G_uni_fst.txt') as f:
  G = k2.Fsa.from_openfst(f.read(), acceptor=False)
G.labels_sym = k2.SymbolTable.from_file('words.txt')
G.aux_labels_sym = k2.SymbolTable.from_file('words.txt')
#G.labels[G.labels >= 3] = 0 # convert symbols with ID >= ID of #0 to eps
G.draw('G_uni.svg', title='G_uni')

G_uni.svg is shown below:

What's more

Please refer to https://github.com/k2-fsa/icefall/blob/master/egs/librispeech/ASR/prepare.sh for how kaldilm is used in icefall.