Abstract
Pronunciation dictionaries are usually expensive and time-consuming to prepare for the computational modeling of human languages, especially when the target language is under-resourced. Northern Chinese dialects are often under-resourced but used by a significant number of speakers. They share the basic sound inventories with Standard Chinese (SC). Also, their words usually share the segmental realizations and logographic written forms with the SC translation equivalents. Hence the pronunciation dictionaries of northern Chinese dialects could be easily available if we were able to predict the tonal realizations of the dialect words from the tonal information of their SC counterparts. This paper applies statistical modeling to investigate the tonal aspect of the related words between a northern dialect, i.e. Jinan Mandarin (JM), and Standard Chinese (SC). Multi-linear regression models were built with between-word pitch distance of JM words as the dependent variable and the following were included as the predictors: SC tonal relations, between-dialect tonal identity, and individual backgrounds. The results showed that tonal relations in SC and between-dialect identity, as predictors featuring the relation between the JM and SC tonal systems, are significant and robust predictors of JM tonal realizations. The speakers' sociolinguistic and cognitive backgrounds, together with the tonal merge and neutral tone information within JM, are important for the prediction of JM tonal realizations and affect the way that between-language predictors take effect. © 2015 Elsevier B.V.
| Original language | English |
|---|---|
| Pages (from-to) | 1-27 |
| Journal | Speech Communication |
| Volume | 76 |
| DOIs | |
| Publication status | Published - 1 Feb 2016 |
| Externally published | Yes |
Bibliographical note
Publication details (e.g. title, author(s), publication statuses and dates) are captured on an “AS IS” and “AS AVAILABLE” basis at the time of record harvesting from the data source. Suggestions for further amendments or supplementary information can be sent to [email protected].Research Keywords
- Cognates
- Individual backgrounds
- Modeling
- Tone
- Translation equivalents
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