Finite-State Transducers (FST) Morphological Analysis System
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A Finite-State Transducers (FST) Morphological Analysis System is a Morphological Analysis System that can solve a Finite-State Transducers (FST) Morphological Analysis Task.
- Example(s):
- Counter-Example(s):
- a Corpus-Based Morphological Analysis System,
- a Finite State Automata (FSA) System,
- a Directed Acrylic Word Graph (DAWG) Morphological Analysis System,
- a Two-Level Morphological Analysis System,
- a Mininum Description Lenth Morphological Analysis System,
- a Paradigm Based Morphological Analysis System,
- a Recurrent Neural Network Model (RNNLM) Based Morphological Analysis System,
- a Stemmer Based Morphological Analysis System,
- See: Finite State Transducer, Natural Language Syntactic Analysis Task, Morphological Tag, Morphological Inflection, Morphological Derivation, Part-of-Speech Tagging System, Word Sense Disambiguation, Minimum Description Length, Zipfian Sparsity, Gibbs Sampling, Non-concatenative Morphology, Allomorphy, Morphophonology, Recurrent Neural Network Language Model.
References
2019
- (Pustejovsky, 2019) ⇒ James Pustejovsky (2019). "Chapter 3. Morphology and Finite-State Transducers". CS-114 . Brandeis University. Retrieved: 2019-01-27.
2015
- (Pustejovsky, 2015) ⇒ James Pustejovsky (2015). "Finite-State Transducers". COSI 114 – Computational Linguistics . Brandeis University.
2014
- (Kalita et al., 2014) ⇒ Nayan Jyoti Kalita, Navanath Saharia, and Smriti Kumar Sinha. (2014). “Morphological Analysis of the Bishnupriya Manipuri Language Using Finite State Transducers.” In: Proceedings of the 15th International Conference on Computational Linguistics and Intelligent Text Processing - Volume:8403. ISBN:978-3-642-54905-2 doi:10.1007/978-3-642-54906-9_16. e-print: arXiv:1404.5357
2008
- (Saranya, 2008) ⇒ S. K. Saranya. (2008). “Morphological Analyzer for Malayalam Verbs.” In: M. Tech Thesis, Amrita School of Engineering, Coimbatore.
- QUOTE: FST is an advanced version of FSA. FST is used to represent the lexicon computationally. It can be done by accepting the principle of two level morphology. The two level morphology represents a word as a correspondence between lexical level and surface level. An FST is represented as a two tape automaton. We can combine lexicon, orthographic rules and spelling variations in the FST to build a morphological analyzer.