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OpenGrm SFst Library: Stochastic Finite-State Transducer Library

SFst is a library for normalizing, sampling, combining, and approximating stochastic (or probabilistic) finite-state transducers. These are weighted finite-state transducers, represented in OpenFst library format, that have the following two properties:

  1. normalized: the weights of the paths into the future from each state sum to Weight::One()1
  2. canonical topology:
    • the states are sorted by input label
    • there may be failure transitions (see phi-labeled transitions) but
      • there is at most one such transition per state
      • there are no failure-transition (and/or epsilon-transition) cycles
    • no assumption is made of general determinism or what transitions must be present on failure (unlike in a canonical n-gram model).

For example, an n-gram model produced by the OpenGrm NGram Library is a stochastic FST2 but many other topologies are possible.

1Computation is done internally assuming the weights are negative log probabilities using Log64Weight. Conversion from the input weight type is done using a WeightConvert functor, pre-defined for common weight types like TropicalWeight and LogWeight.
2Provided the phi_label is specified to match the backoff label, typically 0, of the n-gram model.

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Topic revision: r17 - 2018-07-17 - MichaelRiley
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