Dataset Information

Extracting Phonetic Features From Natural Classes: A Mismatch Negativity Study of Mandarin Chinese Retroflex Consonants.

ABSTRACT: How speech sounds are represented in the brain is not fully understood. The mismatch negativity (MMN) has proven to be a powerful tool in this regard. The MMN event-related potential is elicited by a deviant stimulus embedded within a series of repeating standard stimuli. Listeners construct auditory memory representations of these standards despite acoustic variability. In most designs that test speech sounds, however, this variation is typically intra-category: All standards belong to the same phonetic category. In the current paper, inter-category variation is presented in the standards. These standards vary in manner of articulation but share a common phonetic feature. In the standard retroflex experimental block, Mandarin Chinese speaking participants are presented with a series of "standard" consonants that share the feature [retroflex], interrupted by infrequent non-retroflex deviants. In the non-retroflex standard experimental block, non-retroflex standards are interrupted by infrequent retroflex deviants. The within-block MMN was calculated, as was the identity MMN (iMMN) to account for intrinsic differences in responses to the stimuli. We only observed a within-block MMN to the non-retroflex deviant embedded in the standard retroflex block. This suggests that listeners extract [retroflex] despite significant inter-category variation. In the non-retroflex standard block, because there is little on which to base a coherent auditory memory representation, no within-block MMN was observed. The iMMN to the retroflex was observed in a late time-window at centro-parieto-occipital electrode sites instead of fronto-central electrodes, where the MMN is typically observed, potentially reflecting the increased difficulty posed by the added variation in the standards. In short, participants can construct auditory memory representations despite significant acoustic and inter-category phonological variation so long as a shared phonetic feature binds them together.

SUBMITTER: Fu Z

PROVIDER: S-EPMC8029992 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Heart-rate variability has proved a valid tool in prognosis definition of patients with congestive heart failure (CHF). Previous research has documented Poincaré plot analysis as a valuable approach to study heart-rate variability performance among different subjects. In this paper, we explored the possibility to feed machine-learning (ML) algorithms using unconventional quantitative parameters extracted from Poincaré plots (generated from 24-h electrocardiogram recordings) to classify patients with CHF belonging to different New York Heart Association (NYHA) classes. We performed in sequence the following investigations: first, a statistical analysis was carried out on 9 morphological parameters, automatically measured from Poincaré plots. Subsequently, a feature selection through a wrapper with a 10-fold cross-validation method was performed to find the best subset of features which maximized the classification accuracy for each considered ML algorithm. Finally, patient classification was assessed through a ML analysis using AdaBoost of Decision Tree, k-Nearest Neighbors and Naive Bayes algorithms. A univariate statistical analysis proved 5 out of 9 parameters presented statistically significant differences among patients of distinct NYHA classes; similarly, a multivariate logistic regression confirmed the importance of the parameter ρy in the separability between low-risk and high-risk classes. The ML analysis achieved promising results in terms of evaluation metrics (especially the Naive Bayes algorithm), with accuracies greater than 80% and Area Under the Receiver Operating Curve indices greater than 0.7 for the overall three algorithms. The study indicates the proposed features have a predictive power to discriminate the NYHA classes, to which the features seem evenly correlated. Despite the NYHA classification being subjective and easily recognized by cardiologists, the potential relevance in the clinical cardiology of the proposed features and the promising ML results implies the methodology could be a valuable approach to automatically classify CHF. Future investigations on enriched datasets may further confirm the presented evidence.

Project description:This is the first study to examine the effect of phonetic contexts on children's lexical tone production. Mandarin tones in disyllabic words produced by forty-four 2- to 6-year-old children and twelve mothers were low-pass filtered to eliminate lexical information. Native Mandarin-speaking adults categorized the tones based on the pitch information in the filtered stimuli. All mothers' tones were categorized with ceiling accuracy. Counter to the findings in most previous studies on children's tone acquisition and the prevailing assumption in models of speech development that children acquire suprasegmental features much earlier than segmental features, this study found that children as old as six years of age have not mastered the production of Mandarin tones. Children's tones were judged with significantly lower accuracy than mothers' productions. Tone accuracy improved, while cross subject variability in tone accuracy decreased, with age. Children's tone accuracy was affected by the articulatory complexity of phonetic contexts. Children made more errors in tone combinations with more complex fundamental frequency (F0) contours than tone sequences with simpler F0 changes. When producing disyllabic tone sequences with complex F0 contours, children tended to shift the F0 contour of the first tone to reduce the F0 change, resulting in more tone errors in the first syllable than in the second syllable and showing substantially more anticipatory coarticulation than adults. The results provide further evidence that acquisition of lexical tones is a protracted process in children. Tones produced accurately by children in one phonetic context may not be produced correctly in another phonetic context. Children demonstrate more anticipatory coarticulation in their disyllabic productions than adults, which may be attributed to children's immature speech motor control in tone production, and is presumably a by-product of their inability to accomplish complex F0 changes within the syllable time-frame.

Dataset Information

Extracting Phonetic Features From Natural Classes: A Mismatch Negativity Study of Mandarin Chinese Retroflex Consonants.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets