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الرئيسية > Assessment Of Dysarthric Speec...>الوصف

Assessment Of Dysarthric Speech Through Rhythm Metrics

المصدر: مجلة جامعة الملك سعود - علوم الحاسب والمعلومات
الناشر: جامعة الملك سعود
المؤلف الرئيسي: Dahmani, H. (Author)
مؤلفين آخرين: Selouani, S. A. (Co-Author), O’shaughnessy, D. (Co-Author), Chetouani, M. (Co-Author), Doghmane, N. (Co-Author)
المجلد/العدد: مج25, ع1
محكمة: نعم
الدولة: السعودية
التاريخ الميلادي: 2013
الصفحات: 43 - 49
DOI: 10.33948/0584-025-001-005
ISSN: 1319-1578
رقم MD: 972849
نوع المحتوى: بحوث ومقالات
اللغة: الإنجليزية
قواعد المعلومات: science
مواضيع:
علوم الحاسوب | اللسانيات الحاسوبية | قواعد البيانات
كلمات المؤلف المفتاحية:
Dysarthria | Rhythm | Pairwise Variability Index | Acoustical Analysis | Timing | Nemours Database | Dysarthric Severity
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المستخلص: This paper reports the results of acoustic investigation based on rhythmic classifications of speech from duration measurements carried out to distinguish dysarthric speech from healthy speech. The Nemours database of American dysarthric speakers is used throughout experiments conducted for this study. The speakers are eleven young adult males with dysarthria caused by cerebral palsy (CP) or head trauma (HT) and one non-dysarthric adult male. Eight different sentences for each speaker were segmented manually to vocalic and intervocalic segmentation (176 sentences). Seventy-four different sentences for each speaker were automatically segmented to voiced and non-voiced intervals (1628 sentences). A two-parameters classification related to rhythm metrics was used to determine the most relevant measures investigated through bi-dimensional representations. Results show the relevance of rhythm metrics to distinguish healthy speech from dysarthrias and to discriminate the levels of dysarthria severity. The majority of parameters was more than 54% successful in classifying speech into its appropriate group (90% for the dysarthric patient classification in the feature space (%V, ΔV). The results were not significant for voiced and unvoiced intervals relatively to the vocalic and intervocalic intervals (the highest recognition rates were: 62.98 and 90.30% for dysarthric patient and healthy control classification respectively in the feature space (ΔDNV, %DV).
ISSN: 1319-1578

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