Dataset Information

Sound-sized segments are significant for Mandarin speakers.

ABSTRACT: Do speakers of all languages use segmental speech sounds when they produce words? Existing models of language production generally assume a mental representation of individual segmental units, or phonemes, but the bulk of evidence comes from speakers of European languages in which the orthographic system codes explicitly for speech sounds. By contrast, in languages with nonalphabetical scripts, such as Mandarin Chinese, individual speech sounds are not orthographically represented, raising the possibility that speakers of these languages do not use phonemes as fundamental processing units. We used event-related potentials (ERPs) combined with behavioral measurement to investigate the role of phonemes in Mandarin production. Mandarin native speakers named colored line drawings of objects using color adjective-noun phrases; color and object name either shared the initial phoneme or were phonologically unrelated. Whereas naming latencies were unaffected by phoneme repetition, ERP responses were modulated from 200 ms after picture onset. Our ERP findings thus provide strong support for the claim that phonemic segments constitute fundamental units of phonological encoding even for speakers of languages that do not encode such units orthographically.

SUBMITTER: Qu Q

PROVIDER: S-EPMC3435182 | biostudies-other | 2012 Aug

REPOSITORIES: biostudies-other

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Sound-sized segments are significant for Mandarin speakers.

Qu Qingqing Q Damian Markus F MF Kazanina Nina N

Proceedings of the National Academy of Sciences of the United States of America 20120813 35

Do speakers of all languages use segmental speech sounds when they produce words? Existing models of language production generally assume a mental representation of individual segmental units, or phonemes, but the bulk of evidence comes from speakers of European languages in which the orthographic system codes explicitly for speech sounds. By contrast, in languages with nonalphabetical scripts, such as Mandarin Chinese, individual speech sounds are not orthographically represented, raising the p ...[more]

PMID: 22891321

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Project description:The speech unit segmentation is an important pre-processing step in the analysis of cleft palate speech. In Mandarin, one syllable is composed of two parts: initial and final. In cleft palate speech, the resonance disorders occur at the finals and the voiced initials, while the articulation disorders occur at the unvoiced initials. Thus, the initials and finals are the minimum speech units, which could reflect the characteristics of cleft palate speech disorders. In this work, an automatic initial/final segmentation method is proposed. It is an important preprocessing step in cleft palate speech signal processing. The tested cleft palate speech utterances are collected from the Cleft Palate Speech Treatment Center in the Hospital of Stomatology, Sichuan University, which has the largest cleft palate patients in China. The cleft palate speech data includes 824 speech segments, and the control samples contain 228 speech segments. The syllables are extracted from the speech utterances firstly. The proposed syllable extraction method avoids the training stage, and achieves a good performance for both voiced and unvoiced speech. Then, the syllables are classified into with "quasi-unvoiced" or with "quasi-voiced" initials. Respective initial/final segmentation methods are proposed to these two types of syllables. Moreover, a two-step segmentation method is proposed. The rough locations of syllable and initial/final boundaries are refined in the second segmentation step, in order to improve the robustness of segmentation accuracy. The experiments show that the initial/final segmentation accuracies for syllables with quasi-unvoiced initials are higher than quasi-voiced initials. For the cleft palate speech, the mean time error is 4.4ms for syllables with quasi-unvoiced initials, and 25.7ms for syllables with quasi-voiced initials, and the correct segmentation accuracy P30 for all the syllables is 91.69%. For the control samples, P30 for all the syllables is 91.24%.

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Dataset Information

Sound-sized segments are significant for Mandarin speakers.

Publications

Sound-sized segments are significant for Mandarin speakers.

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