Practical Experiments with Regular Approximation of Context-Free Languages
Bibliographic Data
| ID | 12156401 |
|---|---|
| Authors | Mark-Jan Nederhof (0000-0002-1845-6829, German Research Centre for Artificial Intelligence, corresponding author) |
| Year | 2000 |
| Volume | 26 |
| Issue | 1 |
| Pages | 17-44 |
| Publication date | 2000-03-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Computational Linguistics (JOURNAL) |
| Journal identifiers | ISSN: 0891-2017 • E-ISSN: 1530-9312 |
| Publisher | Association for Computational Linguistics (PUBLISHER • US) |
| DOI | 10.1162/089120100561610 |
| OpenAlex | W2170336504 |
| Language | EN |
| Citations received | 4 |
| References cited | 11 |
Several methods are discussed that construct a finite automaton given a context-free grammar, including both methods that lead to subsets and those that lead to supersets of the original context-free language. Some of these methods of regular approximation are new, and some others are presented here in a more refined form with respect to existing literature. Practical experiments with the different methods of regular approximation are performed for spoken-language input: hypotheses from a speech recognizer are filtered through a finite automaton
Algorithm · Automaton · Construct (python library · Context (archaeology · Context-free grammar · Deterministic finite automaton · Finite-state machine · Grammar · Linguistics · Natural language processing · Programming language · Regular language · Rule-based machine translation · Computer Science · DNA and Biological Computing · Machine Learning and Algorithms · semigroups and automata theory · Artificial Intelligence · Theoretical Computer Science
| Citations per year | 0.17 |
|---|---|
| Citation span | 2003 - 2011 (9) |
| Highly cited | No |