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• W4319080119 startingPage "848" @default.
• W4319080119 abstract "In English, a sentence like He made out our intentions. could be misperceived as He may doubt our intentions. because the coda /d/ sounds like it has become the onset of the next syllable. The nature and occurrence condition of this resyllabification phenomenon are unclear, however. Previous empirical studies mainly relied on listener judgment, limited acoustic evidence, such as voice onset time, or average formant values to determine the occurrence of resyllabification. This study tested the hypothesis that resyllabification is a coarticulatory reorganisation that realigns the coda consonant with the vowel of the next syllable. Deep learning in conjunction with dynamic time warping (DTW) was used to assess syllable affiliation of intervocalic consonants. The results suggest that convolutional neural network- and recurrent neural network-based models can detect cases of resyllabification using Mel-frequency spectrograms. DTW analysis shows that neural network inferred resyllabified sequences are acoustically more similar to their onset counterparts than their canonical productions. A binary classifier further suggests that, similar to the genuine onsets, the inferred resyllabified coda consonants are coarticulated with the following vowel. These results are interpreted with an account of resyllabification as a speech-rate-dependent coarticulatory reorganisation mechanism in speech." @default.
• W4319080119 created "2023-02-04" @default.
• W4319080119 creator A5049702508 @default.
• W4319080119 creator A5075644135 @default.
• W4319080119 date "2023-02-01" @default.
• W4319080119 modified "2023-09-27" @default.
• W4319080119 title "Deep learning assessment of syllable affiliation of intervocalic consonants" @default.
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• W4319080119 doi "https://doi.org/10.1121/10.0017117" @default.
• W4319080119 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36859160" @default.
• W4319080119 hasPublicationYear "2023" @default.
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