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| Content Provider | Springer Nature Link |
|---|---|
| Author | Jansche, Martin |
| Copyright Year | 2004 |
| Abstract | Local deterministic string-to-string transductions arise in natural language processing (NLP) tasks such as letter-to-sound translation or pronunciation modeling. This class of transductions is a simple generalization of morphisms of free monoids; learning local transductions is essentially the same as inference of certain monoid morphisms. However, learning even a highly restricted class of morphisms, the so-called fine morphisms, leads to intractable problems: deciding whether a hypothesized fine morphism is consistent with observations is an NP-complete problem; and maximizing classification accuracy of the even smaller class of alphabetic substitution morphisms is APX-hard. These theoretical results provide some justification for using the kinds of heuristics that are commonly used for this learning task. |
| Starting Page | 439 |
| Ending Page | 455 |
| Page Count | 17 |
| File Format | |
| ISSN | 09258531 |
| Journal | Journal of Logic, Language and Information |
| Volume Number | 13 |
| Issue Number | 4 |
| e-ISSN | 15729583 |
| Language | English |
| Publisher | Kluwer Academic Publishers |
| Publisher Date | 2004-01-01 |
| Publisher Place | Dordrecht |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Boolean satisfiability combinatorial optimization formal languages letter-to-sound rules machine learning natural language processing NP completeness rational transductions Logic Semantics Information Systems Applications (incl.Internet) |
| Content Type | Text |
| Resource Type | Article |
| Subject | Philosophy Computer Science Linguistics and Language |
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