SPELL=openfst
VERSION=1.3.2
SOURCE_HASH=sha512:e346bb908fd6a4f85d41a6f573f301be59dafc1804372390ed6721b54955563a74c7df6a2d80801c043464f54f7a6ddbf0588dd2a986294f3cd9ce8b4ea197e7
SOURCE=$SPELL-$VERSION.tar.gz
SOURCE_DIRECTORY=$BUILD_DIRECTORY/$SPELL-$VERSION
WEB_SITE=http://www.openfst.org
SOURCE_URL[0]=$WEB_SITE/twiki/pub/FST/FstDownload/$SOURCE
LICENSE[0]=APACHE
ENTERED=20071101
KEYWORDS="library pattern"
SHORT="Weighted finite-state transducers"
cat << EOF
OpenFst is a library for constructing, combining, optimizing, and searching
weighted finite-state transducers (FSTs). Weighted finite-state transducers
are automata where each transition has an input label, an output label, and
a weight. The more familiar finite-state acceptor is represented as a
transducer with each transition's input and output label equal. Finite-state
acceptors are used to represent sets of strings (specifically, regular or
rational sets); finite-state transducers are used to represent binary relations
between pairs of strings (specifically, rational transductions). The weights
can be used to represent the cost of taking a particular transition.
FSTs have key applications in speech recognition and synthesis, machine
translation, optical character recognition, pattern matching, string
processing, machine learning, information extraction and retrieval among
others. Often a weighted transducer is used to represent a probabilistic model
(e.g., an n-gram model, pronunciation model). FSTs can be optimized by
determinization and minimization, models can be applied to hypothesis sets
(also represented as automata) or cascaded by finite-state composition, and the
best results can be selected by shortest-path algorithms.
EOF