Interspeech 2008 2008

DOI: 10.21437/interspeech.2008-547

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Implementation and evaluation of fast on-the-fly WFST composition algorithms

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Cited by 6 publications

References 8 publications

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On lattice generation for large vocabulary speech recognition

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2017

2017 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)

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On lattice generation for large vocabulary speech recognition

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2017

2017 IEEE Automatic Speech Recognition and Understanding Workshop (ASRU)

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Generalization of specialized on-the-fly composition

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et al. 2009

2009 IEEE International Conference on Acoustics, Speech and Signal Processing

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In the Weighted Finite State Transducer (WFST) framework for speech recognition, we can reduce memory usage and increase flexibility by using on-the-fly composition which generates the search network dynamically during decoding. Methods have also been proposed for optimizing WFSTs in on-the-fly composition, however, these operations place restrictions on the structure of the component WFSTs. We propose extended on-the-fly optimization operations which can operate on WFSTs of arbitrary structure by utilizing a filter composition. The evaluations illustrate the proposed method is able to generate more efficient WFSTs.

A comparison of dynamic WFST decoding approaches

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2012

2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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