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In Autosegmental-Metrical models of intonational phonology, different types of pitch accents, phrase accents, and boundary tones concatenate to create a set of phonologically distinct phrase-final nuclear tunes. This study asks if an eight-way distinction in nuclear tune shape in American English, predicted from the combination of two (monotonal) pitch accents, two phrase accents, and two boundary tones, is evident in speech production and in speech perception. F0 trajectories from a large-scale imitative speech production experiment were analyzed using bottom-up(k-means) clustering, neural net classification, GAMM modeling, and modeling of turning point alignment. Listeners’ perception of the same tunes is tested in a perceptual discrimination task and related to the imitation results. Emergent grouping of tunes in the clustering analysis, and related classification accuracy from the neural net, show a merging of some of the predicted distinctions among tunes whereby tune shapes that vary primarily in the scaling of final f0 are not reliably distinguished. Within five emergent clusters, subtler distinctions among tunes are evident in GAMMs and f0 turning point modeling. Clustering of individual participants’ production data shows a range of partitions of the data, with nearly all participants making a primary distinction between a class of High-Rising and Non-High-Rising tunes, and with up to four secondary distinctions among the non-Rising class. Perception results show a similar pattern, with poor pairwise discrimination for tunes that differ primarily, but by a small degree, in final f0, and highly accurate discrimination when just one member of a pair is in the High-Rising tune class. Together, the results suggest a hierarchy of distinctiveness among nuclear tunes, with a robust distinction based on holistic tune shape and poorly differentiated distinctions between tunes with the same holistic shape but small differences in final f0. The observed distinctions from clustering, classification, and perception analyses align with the tonal specification of a binary pitch accent contrast {H*, L*} and a maximally ternary {H%, M%, L%} boundary tone contrast; the findings do not support distinct tonal specifications for the phrase accent and boundary tone from the AM model.
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Functional modeling of F0 variation across speakers and between phonological categories: Rising pitch accents in American English
The Autosegmental-Metrical model of American English distinguishes three pitch accents with rising F0 trajectories (H*, L+H*, L*+H), differing in peak alignment and presence vs. absence of a low pitch marking the rise onset. Empirical studies report additional distinctions in the dynamics and scaling of the F0 rise, raising the question of which properties best capture variation among accents. We use functional principal components analysis (FPCA) to examine dynamic properties of accentual F0 trajectories in data from an intonation imitation experiment. F0 trajectories from 70 speakers producing rising accents on the phrase-final (nuclear) accented word were submitted to FPCA. The first three PCs account for 95% of variation in F0 trajectories and each shows significant differences between the three rising accents. Variation in PC1 primarily relates to differences in the overall F0 level of the trajectory, PC2 captures differences in rise shape (scooped vs. domed rise) and PC3 captures fine variation from a following Low phrase accent. Alignment distinctions are distributed across all three PCs. Examination of individual speakers shows all use PC1 and PC2 to some degree to distinguish rising accents, with no trading relations. Rises are variously implemented through level or shape distinctions, to varying degrees across individuals
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- Award ID(s):
- 1944773
- PAR ID:
- 10598518
- Publisher / Repository:
- ISCA
- Date Published:
- Page Range / eLocation ID:
- 1020 to 1024
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.21437/SpeechProsody.2024-206
