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Mowa pacjentki z chorobą Parkinsona w fazie zaawansowanej

100%

Szurek M.

nr 14

137-157

The purpose of this article is to present speech disorders of 91 years old patient suffering from advanced Parkinson’s disease (it is the last stage of the disease when all symptoms are stronger) and to draw attention to the need of mentioning the impact of speech therapy while describing the disease. In the article an author is introducing the patient and her current condition. Mainly it is focused on the speech therapy diagnosis that was based on particular aspects of speech (such as: general condition of the patient, phonation, comprehension of speech and naming, repea- ting, dialogues and storytelling, reading, counting and writing). In the final part, the effectiveness of speech therapy is presented. This publication might become a leading example for other speech therapist on how to manage the therapy for people suffering from these types of disorders in speaking and communication.

End-to-end deep learning approach for Parkinson’s disease detection from speech signals

63%

Quan C. , Ren K. , Luo Z. , Chen Z. , Ling Y.

tom Vol. 42, no. 2

556--574

More than 90% of patients with Parkinson’s disease suffer from hypokinetic dysarthria. This paper proposes a novel end-to-end deep learning model for Parkinson’s disease detection from speech signals. The proposed model extracts time series dynamic features using time-distributed two-dimensional convolutional neural networks (2D-CNNs), and then captures the dependencies between these time series using a one-dimensional CNN (1D-CNN). The performance of the proposed model was verified on two databases. On Database-1, the proposed model outperformed expert features-based machine learning models and achieved promising results, showing accuracies of 81.6% on the speech task of sustained vowel /a/ and 75.3% on the speech task of reading a short sentence (/si shi si zhi shi shi zi/) in Chinese. On Database-2, the proposed model was assessed on multiple sound types, including vowels, words, and sentences. An accuracy of up to 92% was obtained on the speech tasks, which included reading simple (/loslibros/) and complex (/viste/) sentences in Spanish. By visualizing the features generated by the model, it was found that the learned time series dynamic features are able to capture the characteristics of the reduced overall frequency range and reduced variability of Parkinson’s disease sounds, which are important clinical evidence for detecting Parkinson’s disease patients. The results also suggest that the low-frequency region of the Mel-spectrogram is more influential and important than the high-frequency region for Parkinson’s disease detection from speech.

Kształtowanie kompetencji fonologicznych dzieckaw edukacji polonistycznej w okresie wczesnoszkolnym

44%

Kucharska B.

nr 1(23)

55-61

Artykuł dotyczy kluczowej roli edukacji polonistycznej w nauczaniu zintegrowanym, czyli kształtowania kompetencji językowych jako efektu rozwojowej zdolności poznawczej dziecka do odzwierciedlenia i manipulowania dźwiękami mowy. Oczekiwane rezultaty kształcenia to: zdolność do słuchowego rozróżniania fonemów (słuch fonemowy); umiejętność dokonywania operacji na sylabach (analiza i synteza sylabowa), fonemach (analiza i synteza fonemowa) oraz elementach śródsylabowych (identyfikowanie rymów i aliteracji).

The article concerns the central role of elementary education polish studies, or formation of language competence of child; it means a developmental activity to reflect and manipulate the speech sounds. Its main objective is: the ability to distinguish phonemes by ear (phonemic hearing); the ability to perform operations on syllables (syllabic analysis and synthesis), phonemes (phonemic analysis and synthesis) and midsyllable elements (identifying the rhymes and alliteration)