A phonotactic-tonotactic grammar for Tokyo Japanese that clusters by lexical strata offers a good trade-off between model size and likelihood
Bibliographic Data
| ID | 22159274 |
|---|---|
| Authors | Satoru Ozaki (University of Massachusetts Amherst, corresponding author) |
| Year | 2024 |
| Volume | 9 |
| Issue | 1 |
| Pages | 5725 |
| Publication date | 2024-05-15 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Proceedings of the Linguistic Society of America (JOURNAL) |
| Journal identifiers | ISSN: 2473-8689 • E-ISSN: 2473-8689 |
| Publisher | Linguistic Society of America (PUBLISHER • US) |
| DOI | 10.3765/plsa.v9i1.5725 |
| OpenAlex | W4396939151 |
| Language | EN |
| References cited | 4 |
The Japanese lexicon is typically classified into at least three etymological strata: native, Sino-Japanese and foreign words. In Tokyo Japanese, nouns from different strata are known to have different phonotactic as well as tonotactic properties. Should one analyze Tokyo Japanese nouns using a non-clustering grammar that generates all nouns using the same phonological grammar, or should one analyze them using a clustering grammar that generates nouns from different strata using different grammars? In this study, I address this question from a probabilistic and a model selection perspective: the better probabilistic grammar is one that better balances fit to data and the number of parameters in the grammar. Using the UCLA Phonotactic Learner, I train two kinds of MaxEnt grammars that correspond to non-clustering and clustering grammars. I compare the two kinds of grammar using the Bayesian Information Crierion (BIC), and show that the non-clustering grammars make a better trade-off between fit to data and model size than non-clustering grammars. Consequently, different etymological strata of the Tokyo Japanese nominal lexicon are better analyzed as being generated from different MaxEnt grammars than from the same MaxEnt grammar
Grammar · Linguistics · Natural language processing · Phonology · Phonotactics · Computer Science · History · Natural Language Processing Techniques · Philosophy · Speech and dialogue systems · Topic Modeling
| Citation velocity | historical |
|---|---|
| Highly cited | No |