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Please use this identifier to cite or link to this item: http://repositorio.ufla.br/jspui/handle/1/9834

Title: A quantitative model of Yorùbá Speech Intonation using Stem-ML
???metadata.dc.creator???: Àjàdí, Odéjobí Odétúnjí
Keywords: Intonation modelling
Speech synthesis
Quantitative model
Modelagem de entonação
Síntese de fala
Modelo quantitativo
Publisher: Editora da UFLA
???metadata.dc.date???: 1-Sep-2007
Citation: ÀJÀDÍ, O. O. A quantitative model of Yorùbá Speech Intonation using Stem-ML. INFOCOMP: Journal of Computer Science, Lavras, v. 6, n. 3, p. 47-55, Sept. 2007.
Abstract: We present a quantitative model of Standard Yorùbá (SY) intonation; it is designed to have parameters that are linguistically interpretable. The model is built and trained on speech data from a native speaker of SY. The resulting model reproduces the data well: its Root Mean Square prediction error (RMSE) is 14:00 Hz on a test set. We find that intonation is used to mark sentence and phrase boundaries: beginning syllables are systematically stronger, while ending syllables are systematically weaker than the medial syllables. The M tone is the strongest and the H tone is the weakest, though the differences are modest. We see comparable amounts of carry-over and anticipatory co-articulation. The resulting model for SY shows similar characteristics when compared to Mandarin and Cantonese intonation models.
Other Identifiers: http://www.dcc.ufla.br/infocomp/index.php/INFOCOMP/article/view/185
???metadata.dc.language???: eng
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