Filters for Efficient Composition of Weighted Finite-State Transducers

@inproceedings{Allauzen2010FiltersFE,
  title={Filters for Efficient Composition of Weighted Finite-State Transducers},
  author={Cyril Allauzen and Michael Riley and Johan Schalkwyk},
  booktitle={CIAA},
  year={2010}
}
This paper describes a weighted finite-state transducer composition algorithm that generalizes the concept of the composition filter and presents various filters that process epsilon transitions, look-ahead along paths, and push forward labels along epsilon paths. These filters, either individually or in combination, make it possible to compose some transducers much more efficiently in time and space than otherwise possible. We present examples of this drawn, in part, from demanding… 
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References

SHOWING 1-10 OF 16 REFERENCES
An algorithm for fast composition of weighted finite-state transducers
TLDR
This work shows how the size of the decoding graph can be reduced and the necessity of determinizing it can be eliminated by removing the ambiguity associated with transitions to the backoff state or states in G, and shows how this construction can be avoided entirely by performing fast on-the-fly composition of HC and L o G.
A Generalized Dynamic Composition Algorithm of Weighted Finite State Transducers for Large Vocabulary Speech Recognition
We propose a generalized dynamic composition algorithm of weighted finite state transducers (WFST), which avoids the creation of noncoaccessible paths, performs weight look-ahead and does not impose
A specialized on-the-fly algorithm for lexicon and language model composition
This paper presents an algorithm for the composition of weighted finite-state transducers which is specially tailored to speech recognition applications: it composes the lexicon with the language
OpenFst: A General and Efficient Weighted Finite-State Transducer Library
We describe OpenFst, an open-source library for weighted finite-state transducers (WFSTs). OpenFst consists of a C++ template library with efficient WFST representations and over twenty-five
Implementation and evaluation of fast on-the-fly WFST composition algorithms
TLDR
The results show that when using on-the-fly composition with a fully dynamically composed language model component the performance degrades substantially even when avoiding dead-end states, and in these cases the recognition performance can be dramatically improved with the addition of dynamic pushing and state sharing.
Speech Recognition with Weighted Finite-State Transducers
TLDR
General algorithms for building and optimizing transducer models are presented, including composition for combining models, weighted determinization and minimization for optimizing time and space requirements, and a weight pushing algorithm for redistributing transition weights optimally for speech recognition.
Statistical Modeling for Unit Selection in Speech Synthesis
TLDR
A general statistical modeling framework for unit selection inspired by automatic speech recognition is introduced and techniques based on that framework can result in a more accurate unit selection, thereby improving the general quality of a speech synthesizer.
General Algorithms for Testing the Ambiguity of Finite Automata
TLDR
Efficient algorithms for testing the finite, polynomial, and exponential ambiguity of finite automata with i¾?-transitions and an application of these algorithms to an approximate computation of the entropy of a probabilistic automaton are presented.
Finding Common Motifs with Gaps Using Finite Automata
We present an algorithm that uses finite automata to find the common motifs with gaps occurring in all strings belonging to a finite set S = {S1,S2,...,Sr}. In order to find these common motifs we
Semiring Frameworks and Algorithms for Shortest-Distance Problems
  • M. Mohri
  • Computer Science, Mathematics
    J. Autom. Lang. Comb.
  • 2002
TLDR
A generic algorithm for finding single-source shortest distances in a weighted directed graph when the weights satisfy the conditions of the general semiring framework is given.
...
...