Syllabification with Frequent Sequence Patterns - A Language Independent Approach
| Autor: | Camelia Lemnaru, Adrian Bona, Rodica Potolea |
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| Rok vydání: | 2016 |
| Předmět: |
Sequence
Computer science business.industry Syllabification Speech recognition Romanian 020206 networking & telecommunications 02 engineering and technology computer.software_genre language.human_language 0202 electrical engineering electronic engineering information engineering language 020201 artificial intelligence & image processing Artificial intelligence Language independence business computer Natural language processing Word (computer architecture) |
| Zdroj: | KDIR |
| DOI: | 10.5220/0006069703520359 |
| Popis: | In this paper we show how words represented as sequences of syllables can provide valuable patterns for achieving language independent syllabification. We present a novel approach for word syllabification, based on frequent pattern mining, but also a more general framework for syllabification. Preliminary evaluations on Romanian and English words indicated a word level accuracy around 77% for Romanian words and around 70% for English words. However, we believe the method can be refined in order to improve performance. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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